Aksyonov K., Bykov E., Aksyonova O., Goncharova N., Nevolina A. Analysis of Simulation Modeling Systems Illustrated with the Problem of Model Design for the Subject of Technological Logistics (WIP) // Society for Modeling & Simulation International (SCS). 2015 Summer Simulation Multi-Conference (SummerSim'15). Chicago. USA. 26-29 июля, 2015. P. 345-348.

Aksyonov K.A., Antonova A.S., Smoliy E.F., Sysoletin E.G., Sheklein A.A. Application of a models integration module to the cutting slabs problem in a continuous casting machine // Proceedings of The Tenth International Multi-Conference on Computing in the Global Information Technology. 2015. P. 65–72.

Aksyonov K., Bykov E., Aksyonova O., Goncharova N., Nevolina A. Perspectives of Modeling in Metallurgical Production (WIP) // Society for Modeling & Simulation International (SCS). 2015 Summer Simulation Multi-Conference (SummerSim'15). Chicago. USA. 26-29 июля, 2015. P. 341-344.

Albey Erinc, Uzsoy Reha. Lead time modeling in production planning // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.1996-2007.
We use two mathematical models to represent the dependency between workload releases and lead times: a linear programming model with fractional lead times (FLT) and a clearing function (CF) based nonlinear model. In an attempt to obtain a reference solution, a gradient based simulation optimization procedure is used to determine the lead times that, when used in the FLT model, yield the best performance. Results indicate that both FLT and CF models perform well, with CF approach performing slightly better at very high workload scenarios.

Aliyu Hamzat Olanrewaju, Traore Mamadou Kaba. Toward an integrated framework for the simulation, formal analysis and enactment of discrete events systems models // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.3090-3091.
This research proposes a framework that aggregates resources for formal investigation of different properties of systems using disparate analysis methodologies such as simulation, formal methods and code synthesis for real time enactment.

Amblard Frederic, Bouadjio-Boulic Audren, Gutierrez Carlos Sureda, Gaudou Benoit. Which models are used in social simulation to generate social networks? a review of 17 years of publications in JASSS // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.4021-4032.
We examined the articles published in the Journal of Artificial Societies and Social Simulation (JASSS) in between 1998 and 2015 in order to identify the models of social networks that were actually used by the community. After presenting the main models (regular networks, random graphs, small-world networks, scale-free networks, spatial networks), we discuss the evolution of the use of each one of these models. We then present different existing alternatives to those kind of models and discuss the combined use of both simple and more elaborated or data-driven models to different aims along the process of developing agent-based social simulation with realistic synthetic populations.

Amblard F., Daude E., Gaudou B., Grignard A., Hutzler G., Lang C., ... & Taillandier P. (2015). Introduction à NetLogo. Simulation spatiale a base d'agents avec NetLogo // partie 1, 73-112.

Muhammad Arshad, Iftikhar Husain, Atif Zeb, Shahid Maqsood Strategy Formulation for Diagnostics of MRP Driven Production Line through Internal Benchmarking, Simulation and Regression analysis // Technical Journal, University of Engineering and Technology (UET) Taxila, Pakistan Vol. 20(SI) No.II(S)-2015.
A concise strategy is discussed in this paper to frame practical issues that are faced in the diagnostic analysis of a production line. A known model for performance cases is selected as benchmarking framework. Arrival rate, inter arrival time and batch size are selected as process parameters of the system to be analyzed. Focus of the paper is to formulate a diagnostic strategy for the MRP (Material Requirement Planning) driven production line and compare this line with the well known published model in the literature to observe the gaps. Moreover, performance of the strategy under varying input parameters through simulation and regression techniques is also analyzed.

Babina Olga A simulation model of a warehouse of an industrial enterprise for concrete production // BUSINESS INFORMATICS. №1 (31)–2015. P. 41-50.
The article describes a practical case study of building simulation and optimization models for a warehouse of an industrial concrete enterprise. Warehouse system processes are modeled in ExtendSim environment, and enterprise profit is optimized with the use of evolutionary algorithm. The optimization model has been executed by means of Optimizer software integrated into ExtendSim. The modeling purpose is to examine the impact of stock management strategies parameters on warehouse performance and to maximize enterprise profit from product sales. The paper presents the description of the model building process and simulation outputs.

Balaraman V., Athle D., Singh M. (2015). Do Daily Routines Affect Convenience Store Footfalls? – Some Experiments with Agent Based Simulation // To appear in SummerSim 15.

Banitz T., Gras A., Ginovart M. (2015). Individual-based modeling of soil organic matter in NetLogo: Transparent, user-friendly, and open // Environmental Modeling & Software 71, 39-45.

Banos A., Lang C., Marilleau N. (2015). Agent-Based Spatial Simulation with NetLogo. Volume 1.

Barton Russell R. Tutorial: simulation metamodeling // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.1765-1779.
The concept of a metamodel has been an important tool for simulation analysis for forty years. These models of simulation models have the advantage of faster execution, and they can (sometimes) provide insight on the nature of the simulation response as a function of design and input distribution parameters. This introductory tutorial will describe metamodeling uses and associated processes, survey commonly used metamodel types and associated experiment designs, and give a brief description of some recent developments and how they may affect future “mainstream” simulation metamodeling.

Berland M., Wilensky U. (2015). Comparing Virtual and Physical Robotics Environments for Teaching Complex Systems and Computational Literacies // Journal of Science Education and Technology.

Bhakti Stephan Onggo, Mumtaz Karatas. Agent-based model of maritime search operations: a validation using test-driven simulation modelling // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.254-265.
This paper presents a generic agent-based model for maritime search operations which can be used to analyse operations such as search and rescue and patrol. Agent-based simulation (ABS) is a relatively new addition to existing OR techniques. The key elements of an ABS model are agents, their behaviours and their interactions with other agents and the environment. A search operation involves at least two types of agent: a searcher and a target. The unique characteristic of ABS is that we model agents’ behaviours and their interactions at the individual level. Hence, ABS offers an alternative modelling approach to analyse search operations. The second objective of our work is to show how test-driven simulation modelling (TDSM) can be used to validate the agent-based maritime search operation model.

Bhatia A., Singh A., Goyal R. (2015). A Hybrid Autonomic Computing-Based Approach to Distributed Constraint Satisfaction/ Problems // Computers 4(1), 2-23.

Bianchi F., Squazzoni F. Agent‐based models in sociology //Wiley Interdisciplinary Reviews: Computational Statistics. 2015. Т. 7. №. 4. С. 284-306.

Björn Erichsen, Tobias Reggelin, Sebastian Lang, Horst Manner-Romberg. Hierarchical Mesoscopic Simulation Models Of Parcel Service // The 17th International Conference on Harbor, Maritime & Multimodal Logistics Modelling and Simulation. 2015. P. 73-78.

Blum C., Lozano J.A., Davidson P.P. (2015). An Artificial Bioindicator System for Network Intrusion Detection // Artificial Life 21(2), 93-118.

Borges Francisco, Gutierrez-Milla Albert, Suppi Remo, Luque Emilio, Arduino Marylene de Brito. An agent-based model for assessment of Aedes Aegypti pupal productivity // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.159-170.
Dengue is a febrile disease whose main vector transmitter is the Aedes Aegypti mosquito. This disease has an annual register of 50 million infections worldwide. In this paper, we propose an Agent-Based Model for assessment of the pupal productivity of the Aedes Aegypti mosquito. In this model, the reproduction of the mosquito takes into account the productivity of each type of container. The preliminary results show the effects of considering the pupal productivity for the control and prevention of dengue. As a result, we observed that the prevention methods must consider pupal productivity and that the distance between containers might leverage productivity and increase transmission risk. We verify the completeness and functionality of the model through experimentation using Netlogo.

Borodin A., Kiselev Y., Mirvoda S, and Porshnev S. On design of domain-specific query language for the metallurgical industry // Proceedings of 11th Int. Conference BDAS 2015: Beyond Databases, Architectures and Structures: Communications in Computer and Information Science, 26-29 May 2015, Ustron, vol. 521, pp. 505-515.

Bradley Randolph L., Bergman Jennifer J., Noble James S., McGarvey Ronald G. Evaluating a bayesian approach to demand forecasting with simulation // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.1868-1879.
This paper’s contribution is comparing spares forecasting approaches for a well-defined set of airplane parts using a carefully constructed inventory optimization and simulation test environment.

Brailsford Sally C. Hybrid simulation in healthcare: new concepts and new tools // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.1645-1653.

Buda A., Jarynowski A. Agent-based modeling, complex networks and system dynamics – practical aproaches // Матеріали vi всеукраїнської науково-практичної конференції за міжнародною участю «Інформатика та системні науки» (ІСН-2015). 19–21 березня 2015 року. Полтава. Украина.

Butler James; Cosgrove Jason; Alden Kieran; Read Mark; Kumar Vipin; Cucurull‐Sanchez Lourdes; Timmis Jon; Coles Mark (2015). Agent‐based modeling in systems pharmacology // CPT: Pharmacometrics & Systems Pharmacology. 4 (11): 615–629. doi:10.1002/psp4.12018.

Cascalho J., Mabunda P. (2015). Agent-Based Modelling for a Resource Management Problem in a Role-Playing Game // In Progress in Artificial Intelligence (pp. 696-701). Springer International Publishing.

Centeno Martha A., Díaz Kimberly A. Simulating health care systems: a tutorial // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.1835-1849.
This paper is an introduction to discrete event simulation for modeling the operations of healthcare systems. It begins with a brief discussion on the use of simulation to model various areas of healthcare systems. These models were developed to support decision making, to gain a better understanding of the operations of these systems, or to determine how these systems can be improved. The tutorial provides an overview of the simulation modeling process, with a focus on model conceptualization to visualize healthcare systems.

Chapuis Guillaume, Eidenbenz Stephan, Santhi Nandakishore, Park Eun Jung. Simian integrated framework for parallel discrete event simulation on GPUs // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.1127-1138.
Discrete Event Simulation (DES) allows the modelling of ever more complex systems in a variety of domains ranging from biological systems to road networks. The increasing need to model larger systems stresses the demand for efficient parallel implementations of DES engines. Recently, Graphics Processing Units have emerged as an efficient alternative to Central Processing Units for the computation of some problems. Although substantial speedups can be achieved by using GPUs, writing an efficient implementations of given suitable problems often requires in-depth knowledge of the architecture. We present a new framework integrated in the Simian engine. This framework allows modellers to offset some or all handlers to the GPU by efficiently grouping and scheduling these handlers.

Cicirelli F., Nigro C., Nigro L. (2015). Qualitative and quantitative evaluation of stochastic time Petri nets // Proc. of 2nd Int. Workshop on Cyber-Physical Systems (IWCPS'15), Lodz, Poland, pp. 775-784.

Collins A.J., Frydenlund E., Elzie T., Robinson R.M. (2015, April). Agent-based pedestrian evacuation modeling: a one-size fits all approach? // In Proceedings of the Symposium on Agent-Directed Simulation (pp. 9-17). Society for Computer Simulation International.

Cowie G., Hurd M., Sevostianov V., Cundiff M.E., Guerin M.S. (2015). PAVL: Personal Assistance for the Visually Limited. Mexico.

Culciar, A., S. Vasileva. Simulation Studies of the Implementation of Centralized Two-Phase Locking in DDBMS. // 29th European Conference on Modelling and Simulation, May, 26th - 29th, 2015, Albena(Varna), pp.107-114.

D’Alessandro S., Johnson L., Gray D., Carter L. (2015). Consumer satisfaction versus churn in the case of upgrades of 3G to 4G cell networks // Marketing Letters, 26(4), 489-500.

del Sol M., Hill M., James K., Ward R., Prescott P. (2015). Using a Concentrated Heat System to Shock the P53 Protein to Direct Cancer Cells into Apoptosis // New Mexico. Final Report.

Diallo Saikou, Mustafee Navonil, Zacharewicz Gregory. Towards an encyclopedia of modeling and simulation methodology // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.1645-1653.
In this paper, we propose the creation of an encyclopedia of Modeling and Simulation methodologies in order to address these challenges. We survey the structure of several encyclopedias and propose a taxonomical structure and tentative content for the book. We present the characteristics that such a book should have and discuss the potential benefits and areas of growth.

Dickerson M. (2015). Agent-based modeling and NetLogo in the introductory computer science curriculum: tutorial presentation // Journal of Computing Sciences in Colleges, 30(5), 174-177.

Durak Matthew, Durak Nicholas, Goodman Erik D., Till Robert. Optimizing an agent-based traffic evacuation model using genetic algorithms // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.288-299.
Computer simulations are commonly used to model emergencies and discover useful evacuation strategies. The top-down conceptual models typically used for such simulations do not account for differences in individual behavior and how they affect other individuals. To create a more realistic model, this study uses Agent-Based Modeling to simulate the evacuation of an urban population in case of a chlorine spill. Since the agents (each a car and driver) in this model do not behave uniformly, and the initial traffic and spill locations are randomized, optimizing traffic lights is challenging.

Dzikowski J., Hood C. (2015). Modeling cognitive radio networks in NetLogo // In Proceedings of the Conference on Summer Computer Simulation (pp. 1-11). Society for Computer Simulation International.

Eatock Julie, Lord Joanne, Trapero-Bertran Marta, Anagnostou Anastasia. Discrete event simulation of whole care pathways to estimate cost - effectiveness in clinical guidelines // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.1447-1458.
For pragmatic reasons, cost-effectiveness analyses performed for NICE Clinical Guidelines use a piecemeal approach, evaluating only selected aspects of diagnosis, treatment or care. A Whole Pathway approach, considering diagnosis-to-death, may provide more realistic estimates of costs and health outcomes, taking account of the healthcare context and individual risk factors, history and choices for patients with long-term conditions. A patient-level DES model using the characteristics of 12,766 real patients was created to reflect the NICE guideline for Atrial Fibrillation. Of eight topics suggested for inclusion in an update of the guideline, the model was capable of fully answering four topics, and partially answering two topics. The remaining topics were beyond the scope of the model. The model was used by NICE in their recent update of the Atrial Fibrillation Clinical Guidelines.

Fachada N., Lopes V.V., Martins R.C., Rosa A.C. (2015). Towards a standard model for research in agent-based modeling and simulation // Warburg's lens: A mathematical oncology pre-print discussion forum.

Fioroni Marcelo Moretti, Franzese Luiz Augusto G., de Santana Isac Reis, Lelis Pavel Emmanuel Pereira, da Silva Camila Batista, Telles Gustavo Dezem, Quintáns José Alexandre Sereno, Maeda Fábio Kikuda, Varani Rafael. From farm to port: simulation of the grain logistics in brazil // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.1936-1947.
This paper presents a study about soybean and corn multimodal transportation and storage, from farm to port, considering the resources, locations and interferences. A simulation model was developed to evaluate and discover the better option under some future expected scenarios. Train, barges and ships were also considered as part of the logistic process. A localization study was made to feed the model with the best warehouse locations from the logistic point of view, and the model helped to choose which locations should be adopted. The simulation considering the complete chain provided a very precise and insightful answer about the system performance, guiding the future investments in the process.

Flores D.L., Gomez C.M. (2015). Computational modeling of the MAPK pathway using NetLogo // LATIN AMERICAN JOURNAL OF APPLIED ENGINEERING, 1(1), pp.11-17.
In this research, an agent-based modeling and simulation of subsequent events after activation of the Ras molecule in the intracellular MAPK pathway section is presented, using a multi-agent programmable modeling environment called NetLogo.

Fujimoto Richard. Parallel and distributed simulation // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.45-59.
Parallel and distributed simulation is a field concerned with the execution of a simulation program on computing platforms containing multiple processors. This article focuses on the concurrent execution of discrete event simulation programs.

Galante A.T. Intelligent Agent Technologies: The Work Horse of ERP E-Commerce //International Journal of Intelligence Science. – 2015. – 1. 5. – T. 04. – P. 173.

Gammack D. (2015). Using NetLogo as a tool to encourage scientific thinking across disciplines // Journal of Teaching and Learning with Technology, 4(1), 22-39.

Gkiolmas A., Chalkidis A., Papaconstantinou M., Iqbal Z., Skordoulis C. (2015). An alternative use of the NetLogo modeling environment, where the student thinks and acts like an Agent, in order to teach concepts of Ecology // arXiv preprint arXiv:1501.05779. pp. 379-386.

Goel A.K., Joyner D.A. (2015). Impact of a Creativity Support Tool on Student Learning about Scientific Discovery Processes // In Proceedings of the Sixth International Conference on Computational Creativity June (p. 284-291).

Gordo E., Khalaf N., Strangeowl T., Dolino R., Bennett N. (2015). Factors affecting solar power production efficiency // New Mexico. Final Report.

Grgurina N., Barendsen E., van Veen K., Suhre C., Zwaneveld B. (2015, November). Exploring Students' Computational Thinking Skills in Modeling and Simulation Projects: a Pilot Study // In Proceedings of the Workshop in Primary and Secondary Computing Education on ZZZ (pp. 65-68). ACM.

Han Z., Zhang K., Yin H., Zhu Y. (2015, May). An urban traffic simulation system based on multi-agent modeling. In Control and Decision Conference (CCDC), 2015 27th Chinese (pp. 6378-6383). IEEE.

Head Bryan, Hjorth Arthur, Brady Corey, Wilensky Uri.. Evolving agent cognition with netlogo levelspace // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.3122-3123.
We demonstrate a method for using Level Space to simulate agents with complex, evolving cognitive models. We give the agents in a NetLogo predator-prey model “brains,” themselves represented as independent instances of a NetLogo neural network model.

Hjorth A., Brady C., Head B., Wilensky U. (2015). Level Space GUI - Scaffolding Novice Modelers’ Inter-Model Explorations // In proceedings for Interaction Design & Children 2015. Boston, MA.

Hjorth A., Brady C., Head B., Wilensky U. (2015). Thinking Within and Between Levels: Exploring Reasoning with Multi-Level Linked Models // In T. Koschmann, P. Häkkinen, & P. Tchounikine (Eds.), «Exploring the material conditions of learning: opportunities and challenges for CSCL», the Proceedings of the Computer Supported Collaborative Learning (CSCL) Conference Gothenburg, Sweden: ISLS.

Hmelo-Silver C.E., Liu L., Gray S., Jordan R. (2015). Using representational tools to learn about complex systems: A tale of two classrooms // Journal of Research in Science Teaching, 52(1), 6-35.

Horio Brant M., Kumar Vivek, DeCicco Anthony H. An agent-based approach to modeling airlines, customers, and policy in the u.s. air transportation system // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.336-347.
We present a modeling approach to assist policymakers in identifying impacts on the U.S. air transportation system (ATS) due to the implementation of potential policies and the introduction of new technologies. Our approach simulates the responses of U.S. commercial airlines and other ATS stakeholders to these changes, which cumulatively result in consequences to the ATS.

Hussain Talib S., Tiberio Lisa, VanderZee Evan. Hierarchical, extensible search-based framework for airlift and sealift scheduling using discrete event simulation // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.2342-2353.
We present an airlift constraint scheduler capability implemented using the framework, describe ongoing prototype efforts to apply the framework across other levels of Analysis of Mobility Platform, and discuss future potential enhancements.

Il-Chul Moon, Jang Won Bae, Junseok Lee, Doyun Kim, Hyunrok Lee, Taesik Lee, Won-Chul Cha, Ju-Hyun Kim, Gi Woon Kim. EMSSim: emergency medical service simulator with geographic and medical details // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.1272-1284.
This paper introduces EMSSim that is an agent-based simulation of emergency medical services during disasters. We developed EMSSim to encompass the disaster victims’ pass-ways from their rescues to their definitive care. This modeling scope resulted that our model delivers the detailed geographical and medical modeling which are often modeled separately. This is an effort to fill the gap between the prehospital delivery and the in-hospital care over the disaster period.

Izquierdo L.R., Olaru D., Izquierdo S.S., Purchase S., Soutar G.N. (2015). Fuzzy Logic for Social Simulation Using NetLogo // Journal of Artificial Societies and Social Simulation, 18 (4) 1.

Jain Ajitesh, Liu Mengmeng, Fujimoto Richard, Crittenden John, Kim Jongchan, Lu Zhongming. Towards automating the development of federated distributed simulations for modeling sustainable urban infrastructures // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.2668-2679.
The study of sustainable urban systems requires analysis of interdependencies and relationships among infrastructures and social processes. Federated simulations using the High Level Architecture is a natural approach to modeling such systems-of-systems. Simulations interoperability requires a common structure and meaning of shared data represented in a Federation Object Model (FOM). Developing the FOM and modifying simulations to comply with the FOM requires a significant amount of time and effort. We describe a system to automate portions of this task. Specifically we present a workflow by which existing simulations can be integrated in a semi-automated process to reduce the manual labor required. We use SysML to describe entities of the federated distributed simulation. These descriptions are used for automatic generation of the FOM and code required for HLA integration. Finally we present a case study applying this methodology to create a federated distributed simulation to study sustainable urban growth.

Jeewan A., Hussain R. (2015). Minimal Energy Consumption by WSN Nodes during Communication using LEACH and NetLogo in Intelligent Greenhouse // International Journal of Advanced Research in Computer Science, Volume 6, No. 6.

Jerry K., Yujun K., Kwasi O., Enzhan Z., Parfait T. (2015). NetLogo implementation of an ant colony optimisation solution to the traffic problem // Intelligent Transport Systems, IET, 9(9), 862-869.

Jian Nanjing, Henderson Shane G. An introduction to simulation optimization // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.1780-1794.
In this tutorial we give an introduction to simulation optimization, covering its general form, central issues and common problems, basic methods, and a case study. Our target audience is users with experience in using simulation, but not necessarily experience with optimization. We offer guiding principles, and point to surveys and other tutorials that provide further information.

Jiang G., Liu X., Wang Y. (2015). An Agent-based Simulation System for Evolution of Interplay between E-Commerce Vendor and Consumers // International Journal of Hybrid Information Technology, 8(4), pp.81-88.

Jiang G., Wang Y., Zhang N. (2015). Evolution of the Interplay Between E-Commerce Vendor and Consumers // In LISS 2014 (pp. 1243-1247). Springer Berlin Heidelberg.

Jimenez-Romero C., Sousa-Rodrigues D., Johnson J.H. (2015). A Model for Foraging Ants, Controlled by Spiking Neural Networks and Double Pheromones // Proceedings of the UK Workshop on Computational Intelligence (UKCI 2015) Conference, at Exeter.

Kahn K. (2015). An Introduction to Agent-Based Modeling: Modeling Natural, Social, and Engineered Complex Systems with NetLogo // Physics today, 68(8), 55.
Kaligotla Chaitanya, Yucesan Enver, Chick Stephen E. An agent based model of spread of competing rumors through online interactions on social media // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.3088-3089.
The continued popularity of social media in the dissemination of ideas and the unique features of that channel create important research opportunities in the study of rumor contagion. Using an agent-based modeling framework, we study agent behavior in the spread of competing rumors through an endogenous costly exercise of measured networked interactions whereby agents update their position, opinion or belief with respect to a rumor, and attempt to influence peers through interactions, uniquely shaping group behavior in the spread of rumors. . It should be pointed out that this research is still in its nascent stages and much needs to be further investigated.

Ki-Hwan G. Bae, Long Zheng, Imani Farhad. A simulation analysis of the vehicle axle and spring assembly lines // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.2249-2259.
The aim of this study is to provide viable manufacturing plans to improve productivity, and we propose several alternative system component changes to reach the desired throughput level as well as determine the corresponding optimal system configurations. Sensitivity analyses were conducted to measure the effects of various factors such as arrival rate, batch size, and operator resource on throughput, and consequently to find the best scenario. The results of the proposed simulation model demonstrated potential impacts on production capacity increase by considering multiple operational factors while applying feasible improvement strategies.

Kuznetsov A., Keizer A. Simulation for assessment of the interface between port traffic and dredging activity // Proceedings of the 15th International Conference Reliability and Statistics in Transportation and Communication (RelSta’15), 21-24 October 2015. - Riga, Latvia, 2015. - P. 41.
Lal Tarun Mohan, Roh Thomas, Huschka Todd. Simulation based optimization: applications in healthcare // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.1261-1271.
In this paper, we discuss the methodology and applications of simulation based optimization, highlighting advantages, challenges and opportunities of using this method in healthcare.

Law Averill M. Statistical analysis of simulation output data: the practical state of the art // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.1810-1819.
One of the most important but neglected aspects of a simulation study is the proper design and analysis of simulation experiments. In this tutorial we give a state-of-the-art presentation of what the practitioner really needs to know to be successful. We will discuss how to choose the simulation run length, the warmup-period duration (if any), and the required number of model replications (each using different random numbers). The talk concludes with a discussion of three critical pitfalls in simulation output-data analysis.

Lawson Barry, Leemis Lawrence M. Discrete-event simulation using R // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.3502-3513.
R is a free software package with extensive statistical capability, customizable graphics, and both imperative and vectorized programming capabilities. In this paper, we present an R function named ssq which we wrote to simulate a single-server queue, and we provide several illustrations showing its use as an exemplar for using R in an introductory simulation course. All of the code to analyze the output from ssq uses functions from the base distribution of R.

Lee Young M., Horesh Raya, Liberti Leo. Simulation and optimization of energy efficient operation of HVAC system as demand response with distributed energy resources // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.991-999.
In this paper, we describe a model predictive control framework that optimally determines control profiles of the HVAC system as demand response. A Nonlinear Autoregressive Neural Network is used to model the thermal behavior of the building zone and to simulate various HVAC control strategies.

Levin Scott, Garifullin Maxim. Simulating wait time in healthcare: accounting for transition process variability using survival analyses // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.1252-1260.

Li R., Gao H. W., Song, L., Sun L.P., Wang L. (2015). Coordination Game with Non-exclusive Convention on the Ring Network and the Study // Journal of Qingdao University (Natural Science Edition), 1, 004.

Li Haobin, Zhu Yinchao, Chen Yixin, Pedrielli Giulia, Pujowidianto Nugroho A. The object-oriented discrete event simulation modeling: a case study on aircraft spare part management // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.3514-3525.

Liu Elvis S. On the scalability of agent-based modeling for medical nanorobotics // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.1427-1435.
To further study the application of nanorobotics in medicine, this paper focuses on the design of an agent-based simulation system, which is a computer simulation composed of multiple interacting intelligent agents within an environment. Agentbased modeling has been used to solve problems that are difficult for an individual agent to solve.

Liu Zhengchun, Rexachs Dolores, Luque Emilio, Epelde Francisco, Cabrera Eduardo. Simulating the micro-level behavior of emergency department for macro-level features prediction // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.171-182.
In this paper we present a layer-based application framework to discover knowledge of an emergency department system through simulating micro-level behaviors of its components to facilitate a systematic understanding. Finally, case studies are used to demonstrate the potential use of the proposed approach. Results show that the proposed framework can significantly reflect the non-linear association between micro-level behavior and macro-level features.

Lungeanu A., Sullivan S., Wilensky U., Contractor N.S. (2015). A computational model of team assembly in emerging scientific fields // In L. Yilmaz, W.K.V. Chan, I. Moon, T.M.K. Roeder, C. Macal, & M.D. Rossetti (Eds.). Proceedings of the 2015 Winter Simulation Conference.

Lychkina N.N., Morozova Y.A. Agent based modeling of pension system development processes // Proceedings of SAI Intelligent Systems Conference 2015 (IntelliSys 2015), 10–11 November 2015, London, UK. P. 857–862.

Ma Zhiyuan, Fukuda Munehiro. A multi-agent spatial simulation library for parallelizing transport simulations // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.115-126.
To support distributed-memory parallelization for multi-agent models, we have developed the MASS (multi-agent spatial simulation) library. This paper presents how to parallelize MATSim (multi-agent transport simulation) using the MASS library and demonstrates the library’s portability and execution performance in practical transport simulations.

Ma Y., Li Y. (2015). Conceptual Research on Decision Making Meetings for Urban Water Management // International Review for Spatial Planning and Sustainable Development, Vol.3, No.3, (2015), 16-24 ISSN: 2187-3666 (online).

Manzo G., Baldassarri D. (2015). Heuristics, Interactions, and Status Hierarchies An Agent-based Model of Deference Exchange // Sociological Methods Research 44(2), 329-387.

Marshall P. System dynamics modeling of the impact of Internet of Things on intelligent urban transportation // Proc. Regional Conf. ITS, Los Angeles, CA, 2015.

Mayrhofer C. (2015). Performance, Scale & Time in Agent-based Traffic Modelling with NetLogo // GI_Forum, 2015, 567-570.

Menth Megan, Stamm Jessica L. Heier. An agent-based modeling approach to improve coordination between humanitarian relief providers // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.3116-3117.
This research aims to improve upon the current practices of facility placement coordination by drawing on data from the 2015 earthquake in Nepal. We develop an agent-based simulation model with data from this event, and extend our findings to provide new insights about humanitarian decision making and coordination in regard to the facility location problem.

Micu L.A., Ciutacu I. (2015). EU Vs. China: Is Agriculture the Way towards Sustainability? Case Study Using Agent-based Models // Procedia Economics and Finance, 27, 607-611.

Mittal Anuj, Krejci Caroline C. A hybrid simulation model of inbound logistics operations in regional food supply systems // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.1549-1560.
In this paper, we describe a hybrid simulation model of the inbound logistics operations of a food hub. Using this model, we observe the scheduling behavior of the producers under different conditions and explore the effectiveness of implementing incentives to encourage producers to schedule their deliveries in advance.

Momen S. and Tabassum K.T. (2015). Group Performance in a Swarm of Simulated Mobile Robots // ULAB Journal of Science and Engineering, vol 6, no. 1, pp: 25 - 31, ISSN: 2079-4398 (print), ISSN: 2414-102X (online) .
In this paper, we look at how swarms of simulated mobile robots (i.e. mobile agents) carry out the decision of doing a particular task in an artificial world. In this paper, we present an agent based modelwherein groups of mobile agents make decisions based on some simple rules.

Monks Thomas, Pearn Kerry, Allen Michael. Simulation of stroke care systems // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.1391-1402.
This paper presents an overview of simulation methodology to tackle logistical and capacity planning problems in stroke. Four contributions are made to accelerate studies in this area.

Montevechi Jose Arnaldo Barra, Silva Elisa Maria Melo, da Costa Ana Paula Rennу, de Sena David Custуdio, Scheidegger Anna Paula G. Hybrid simulation of production process of Pupunha palm // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.1561-1572.
This work simulated some alternatives of dynamic allocation of additional human resources in a company that produces various products from Pupunha palm. Its goal was to increase the average amount of trays produced per day in this line through a hybrid application of discrete event and agent-based simulation. Two different decision-making forms were proposed to find out which workstation should have received an additional operator.

Moon S., Han Y. (2015). An Agent Based Model for the Study on Undergraduate’s Choice of Seat and Seat Distribution // Advanced Science and Technology Letters Vol.103 (Education 2015), pp.162-167.
This paper presents an agent based model for the study on undergraduate's choice of seat and seat distribution. The proposed model will be helpful to analyze both the factors influencing the seat selection and the distribution of the finished seat.

Morgareidge David L. Comprehensive operational modeling and simulation policy development: private sector healthcare systems and the us military healthcare system // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.1415-1426.

Muller Dan. Automod – modeling the real-world complexities of manufacturing, distribution, and logisitics systems for over 30 years // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.4137-4148.
The AutoMod product suite from Applied Materials has been used on thousands of projects empowering engineers and managers to make the best decisions. AutoMod power lies in its performance and details in modeling large and complex manufacturing, distribution, automation and logistic operations, leaving the competition behind. AutoMod supports hierarchical model construction allowing users to reuse model components, decreasing the time required to build models.

Mulyukin A.A., Kossovich T., Perl I.A. Effective execution of systems dynamics models // Proc. 19th Conf. of Open Innovations Association FRUCT, 2016, pp. 358–364.

Munteanu A.C. (2015). Knowledge Spillovers of FDI // Procedia Economics and Finance, 32, 1093-1099.

Mustafee Navonil, Powell John, Brailsford Sally C., Diallo Saikou, Padilla Jose, Tolk Andreas. Hybrid simulation studies and hybrid simulation systems: definitions, challenges, and benefits // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.1678-1692.
Most dynamic simulations have a notion of time, how do we realize a unified representation of simulation time across methodologies, techniques and packages, and how do we prevent causality during inter-model message exchange? These are but some of the questions which we found to be asking ourselves frequently, and this panel paper provided a good opportunity to stimulate a discussion along these lines and to open it up to the M&S community.

Nechaevskiy A.V., Pryahina D.I., Trofimov V.V. Usage of data of a Tier1 site monitoring for simulation of the file distribution strategies // CEUR Workshop Proceedings, ISSN 1613-0073, Vol.1536, 2015, р.173-178.

Nolting B.C., Hinkelman T.M., Brassil C.E., Tenhumberg B. (2015). Composite random search strategies based on non-directional sensory cues // Ecological Complexity 22, 126-138.

Novak Ana, Tracey Luke, Nguyen Vivian, Johnstone Michael, Le Vu, Creighton Doug. Evaluation of tender solutions for aviation training using discrete event simulation and best performance criteria // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.2680-2691.
This paper describes a novel discrete event simulation (DES) methodology for the evaluation of aviation training tenders where performance is measured against “best performance” criteria. The objective was to assess and compare multiple aviation training schedules and their resource allocation plans against predetermined training objectives. This research originated from the need to evaluate tender proposals for the Australian Defence Aviation Training School that is currently undergoing aviation training consolidation and helicopter rationalization.

Okolnishnikov Victor, Rudometov Sergey, Zhuravlev Sergey. A specialized library for simulation of coal mining in flat-lying coal seam // Proc. of the 27th the European Modeling and Simulation Symposium (EMSS 2015), Bergeggi, Italy, September 21–23, 2015, P. 425–429.

Olson Kara A., Overstreet C. Michael. Enhancing understanding of discrete event simulation models through analysis // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.472-483.
This work extends current research in model analysis and program understanding to assist modelers in obtaining additional insight into their models and the systems they represent. Given a particular simulation implementation, this research demonstrates the feasibility of automatically-derived observations that could potentially enhance a model builder or model user’s understanding of their models.

Olsvicova K., Prochazka J., Danielisova A. (2015). Reconstruction of Prehistoric Settlement Network Using Agent-Based Model in NetLogo // In Highlights of Practical Applications of Agents, Multi-Agent Systems, and Sustainability-The PAAMS Collection (pp. 165-175). Springer International Publishing.

Ordonez Medina S.A. Personalized multi-activity scheduling of flexible activities // hEART 2015: 4th Symposium of the European association for research in transportation (9-11 September, Lyngby, Denmark): [web] / European Association for Research in Transportation.

Ososkov G.A., Korenkov V.V., Nechaevskiy A.V., Pryahina D.I., Trofimov V.V., Uzhinskiy A.V., Balashov N.A. Web-Service development of the grid-сloud simulation tools // Procedia Computer Science, Vol.66, 2015, p.533-539.

Pepino Alessandro, Torri Adriano, Mazzitelli Annunziata, Tamburis Oscar. A simulation model for analyzing the nurse workload in a university hospital ward // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.1367-1378.
The aim of the present work is to propose a prototype simulation of a hospital ward which permits the study of the workload and task distribution among nursing and auxiliary personnel. In our study, we took both X a generic ward in a complex healthcare structure (University Hospital “Federico II” – Naples, Italy) and a case study of a hospital immunology department as reference models. Both analyses were carried out together with a team of expert head nurses and following a specific simulation model developed in the Simul8 environment, which allowed the calculation of patient assistance timing as well as the efficiency of personnel use depending on the patient autonomy.

Pereda M., Poza D., Santos J.I., Galán J.M. (2015). Quality Uncertainty and Market Failure: An Interactive Model to Conduct Classroom Experiments // In International Joint Conference (pp. 549-557). Springer International Publishing.

Plinere D., Aleksejeva L. Agent system application as a tool for inventory management improvement // Proceedings of Eighth International Conference on Soft Computing, Computing with Words and Perceptions in System Analysis, Decision and Control (ICSCCW-2015), Turkey, Antalya, Sep. 2015, pp. 157-166.

Polhill J.G. (2015). Extracting OWL Ontologies from Agent-Based Models: A Netlogo Extension // Journal of Artificial Societies and Social Simulation, 18(2), 15.
This paper presents arguments that Netlogo does not have the same semantic challenges to automated ontology extraction, and describes an extension to Netlogo (5.0) using the OWL-API (3.1.0) that extracts state and structure ontologies from an existing Netlogo model.

Priest B., Vuksani E., Wagner N., Tello B., Carter K., Streilein W. (2015). Agent-Based Simulation in Support of Moving Target Cyber Defense Technology Development and Evaluation // In Proceedings of the 2015 ACM Spring Simulation Multi-Conference - Communications and Networking Simulation Symposium, Alexandria, VA, April, 2015.

Prochazka J., Cimler R., Olsevicova K. (2015). Pedestrian Modelling in NetLogo // In Emergent Trends in Robotics and Intelligent Systems (pp. 303-312). Springer International Publishing.

Prochazka J., Olsevicova K. (2015). Monitoring Lane Formation of Pedestrians: Emergence and Entropy // In Intelligent Information and Database Systems (pp. 221-228). Springer International Publishing. [HTML]

Rajamanickam Gayathri Devi, Ramadurai Gitakrishnan. Simulation of truck congestion in chennai port // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.1904-1915.
The primary focus of this study is to understand the current port operating condition and recommend short term measures to improve traffic condition in the port of Chennai. The cause of congestion is identified based on the data collected and observation made at port gates as well as at terminal gates in Chennai port. A simulation model for the existing road layout is developed in micro-simulation software VISSIM and is calibrated to reflect the prevailing condition inside the port.

Ramli N.R., Razali S., Osman M. (2015, August). An overview of simulation software for non-experts to perform multi-robot experiments // In Agents, Multi-Agent Systems and Robotics (ISAMSR), 2015 International Symposium on (pp. 77-82). IEEE.

Robinson Stewar. A tutorial on conceptual modeling for simulation // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.1820-1834.

Robinson Stewart, Arbez Gilbert, Birta Louis G., Tolk Andreas, Wagner Gerd. Conceptual modeling: definition, purpose and benefits // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.1678-1692.
Over the last decade there has been a growing interest in «conceptual modeling» for simulation. This is signified by a greater intensity of research and volume of papers on the topic. What is becoming apparent, however, is that when it comes to conceptual modeling there are quite different views and opinions. These differences may be beneficial for creating a debate that takes the field forward, but they can also lead to confusion. The purpose of this panel is for leading researchers to identify and discuss their views on conceptual modeling. In particular we will debate the definition, purpose and benefits of conceptual modeling for the field of simulation. Through the discussion we hope to highlight common ground and key areas of difference.

Rotenberry J.T., Swanger E., Zuk M. (2015). Alternative reproductive tactics arising from a continuous behavioral trait: callers versus satellites in field crickets // American Naturalist 185:469-490. DOI: 10.1086/680219.

Sahoo Kamalakanta, Mani Sudhagar. GIS based discrete event modeling and simulation of biomass supply chain abstract // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.967-978.
A consistent, reliable and low cost biomass supply chain is crucial for a sustainable biorefinery. Spatial and temporal variations in biomass yield, weather risk, transport network, machine capacity significantly impacts logistics cost and supply chain performances. The objectives of the study are to develop a sustainable biomass supply chain modeling framework coupled with GIS (Geographic Information System) to estimate feedstock flow rate and delivered cost. The supply chain model was developed and implemented in discrete event simulation platform and tested with Miscanthus crop (biomass) supply chain for 10 years from strip-mined lands in Ohio.

Sanchez Paul J., Sanchez Susan M. A scalable discrete event stochastic agent-based model of infectious disease propagation // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.151-158.
We propose a new stochastic model of infectious disease propagation. This model tracks individual outcomes, but does so without needing to create connectivity graphs for all members of the population. This makes the model scalable to much larger populations than traditional agent-based models have been able to cope with, while preserving the impact of variability during the critical early stages of an outbreak.

Sanchez Susan M., Hong Wan. Work smarter, not harder: a tutorial on designing and conducting simulation experiments // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.1795-1809.
In this tutorial, we demonstrate the basic concepts important for design and conducting simulation experiments, and provide references to other resources for those wishing to learn more. This tutorial (an update of previous WSC tutorials) will prepare you to make your next simulation study a simulation experiment.

Santhi Nandakishore, Eidenbenz Stephan, Liu Jason. The Simian concept: parallel discrete event simulation with interpreted languages and just-in-time compilation // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.3013-3024.
We introduce Simian, a family of open-source Parallel Discrete Event Simulation (PDES) engines written using Lua and Python. Simian reaps the benefits of interpreted languages—ease of use, fast development time, enhanced readability and a high degree of portability on different platforms—and, through the optional use of Just-In-Time compilation, achieves high performance comparable with the state-of-the-art PDES engines implemented using compiled languages such as C or C++. This paper describes the main design concepts of Simian, and presents a benchmark performance study, comparing four Simian implementations against a traditionally compiled simulator, MiniSSF, written in C++.

Sargent Robert G. An introductory tutorial on verification and validation of simulation models // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.1729-1740.
Model verification and validation are defined, and why model verification and validation are important is discussed. A graphical paradigm that shows how verification and validation are related to the model development process and a flowchart that shows how verification and validation is part of the model development process are presented and discussed. The three approaches to deciding model validity are described. Comments are made on the importance of model accuracy and documentation. An overview of conducting verification and validation is presented and a recommended procedure for verification and validation is given.

Sargent Robert G., Goldsman David M., Yaacoub Tony. Use of the interval statistical procedure for simulation model validation // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.60-72.
In this tutorial we discuss the use of a recently published statistical procedure for the validation of models that have their required model accuracy specified as a range, often called the acceptable range of accuracy. This new statistical procedure uses a hypothesis test of an interval, considers both Type I and Type II errors through the use of the operating characteristic curve, and provides the model builder’s risk curve and the model user’s risk curve. A detailed procedure for validating simulation models using this interval hypothesis test is given, computer software developed for this procedure is briefly described, and examples of simulation model validation using the procedure and software are presented.

Sarjoughian Hessam S., Alshareef Abdurrahman, Lei Yonglin. Behavioral DEVS metamodeling // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.2788-2799.

Savage Sam L., Thibault John Marc. Towards a simulation network or the medium is the Monte Carlo (with apologies to marshall mcluhan) // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.4126-4133.
This article describes how such data may foster the creation of networks of simulations that bring stochastic modeling to general management.

Schriber Thomas J., Brunner Daniel T., Smith Jeffrey S. Inside discrete-event simulation software: how it works and why it matters // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.1-15.
This paper provides simulation practitioners and consumers with a grounding in how discrete-event simulation software works. Topics include discrete-event systems; entities, resources, control elements and operations; simulation runs; entity states; entity lists; and their management. The implementations of these generic ideas in AutoMod, SLX, ExtendSim, and Simio are described. The paper concludes with several examples of “why it matters” for modelers to know how their simulation software works, including discussion of AutoMod, SLX, ExtendSim, Simio, Arena, ProModel, and GPSS/H.

Sengupta P., Dickes A., Farris A.V., Karan A., Martin D., Wright M. (2015). Programming in K-12 science classrooms // Communications of the ACM, 58(11), 33-35.

Serova E. (2015), Hybrid Intelligent Systems and Models for Architectural Design of Management System // Proceedings of the Symposium Automated systems and technologies, Peter the Great St. Petersburg Polytechnic University, Leibniz Universitдt Hannover, St. Petersburg, pp. 51-58.

Serova E., Krichevsky M. (2015), Intelligent Models and Systems in Spatial Marketing Research // The Electronic Journal Information Systems Evaluation, vol. 18 Iss. 2, pp.160-172.

Shook E., Wren C., Marean C.W., Potts A.J., Franklin J., Engelbrecht F., ... & Esler K.J. (2015, July). Paleoscape model of coastal South Africa during modern human origins: progress in scaling and coupling climate, vegetation, and agent-based models on XSEDE // In Proceedings of the 2015 XSEDE Conference: Scientific Advancements Enabled by Enhanced Cyberinfrastructure (p. 2). ACM.

Siddique O., Steven F. Railsback and Volker Grimm. (2015). Agent-Based and Individual-Based Modelling: A Practical Introduction // Pakistan Development Review, 54(1), 76-77.

Singh M., Balaraman V. (2015). Exploring Norm Establishment and Spread in Different Organizational Structures Using an Extended Axelrod Model // Spring Sim 15, Proceedings of the 2015 Spring Sim Simulation Multiconference.

Sprock Timothy, McGinnis Leon F. A simulation optimization framework for discrete event logistics systems (DELS) // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.2776-2787.
For large-scale, complex systems, both simulation and optimization methods are needed to support system design and operational decision making. Integrating the two methodologies, however, presents a number of conceptual and technical problems. This paper argues that the required integration can be successfully achieved, within a specific domain, by using a formal domain specific language for specifying instance problems and for structuring the analysis models and their interfaces. The domain must include a large enough class of problems to justify the resulting specialization of analysis models.

Stetsenko I.V. Petri-Object Simulation: Software Package and Complexity / I. Stetsenko, V. Dorosh, A. Dyfuchyn // Proceedings of the 8th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications. Warsaw, 2015. P. 381-385.

Stetsenko Inna V., Dorosh Vitaliy I., Dyfuchyn Anton. Petri-object simulation: software package and complexity // Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS), 2015 IEEE 8th International Conference. – IEEE, 2015. –Vol.1. – P.381-385.

Sturrock David T. Tutorial: tips for successful practice of simulation // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.1756-1764.
A simulation project is much more than building a model and the skills required for success go well beyond knowing a particular simulation tool. A 30 year veteran discusses some important steps to enable project success and some cautions and tips to help avoid common traps. This content is similar to presentations given at previous WSC conferences.

Thiesing Renee M., Pegden C. Dennis. Introduction to Simio // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.4090-4099.
This paper describes the Simio modeling system that is designed to simplify model building by promoting a modeling paradigm shift from the process orientation to an object orientation. Simio is a simulation modeling framework based on intelligent objects. The intelligent objects are built by modelers and then may be reused in multiple modeling projects. Although the Simio framework is focused on object-based modeling, it also supports a seamless use of multiple modeling paradigms including event, process, object, systems dynamics, agent-based modeling, and Risk-based Planning and scheduling (RPS).

Thiesing Renee M., Pegden C. Dennis. Simio applications in scheduling // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.4150-4159.
Simulation has traditionally been applied in system design projects where the basic objective is to evaluate alternatives and predict and improve the long term system performance. In this role simulation has become a standard business tool with many documented success stories. Beyond these traditional system design applications simulation can also play a powerful role in scheduling by predicting and improving the short term performance of a system. However these applications have a number or unique requirements which traditional simulation tools do not address. Simo has been designed from the ground up with a focus on both traditional applications as well as scheduling, with the basic idea that a single Simio model can serve both purposes.

Timm Ingo J., Lorig Fabian. Logistics 4.0 – a challenge for simulation // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.3118-3119.
This paper aims at discussing two integrating approaches to simulate decision makers and logistic processes in the context of Logistics 4.0.

Timm Ingo J., Lorig Fabian. A survey on methodological aspects of computer simulation as research technique // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.2704-2715.

Trab S., Bajic E., Zouinkhi A., Abdelkrim M.N., Chekir H., Ltaief R.H. (2015). Product Allocation Planning with Safety Compatibility Constraints in IoT-based Warehouse // Procedia Computer Science, 73, 290-297.

Troitzsch K.G. (2015). What One Can Learn from Extracting OWL Ontologies from a NetLogo Model That Was Not Designed for Such an Ex-Ercise // Journal of Artificial Societies and Social Simulation, 18(2), 14.

Uemura M., Matsushita H., Kraetzschmar G.K. (2015, November). Path Planning with Slime Molds: A Biology-Inspired Approach // In Neural Information Processing (pp. 308-315). Springer International Publishing.

Ursini Edson L., Martins Paulo S., Timoteo Varese S., Massaro Flavio R. Modeling and simulation applied to link dimensioning of stream ip traffic with incremental validation // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.3049-3060.
In this paper, we present a methodology for dimensioning the link capacity and packet delay in stream, IP multi-service networks with QoS requirements, in which discrete-event simulation is essential. The model may be used in the lack of enough reliable real-world data, since it is initially validated by an analytical model and then augmented step by step. The approach can be made more reliable if measured values are used. We show that the incremental approach allows a significant reduction in simulation time without significant loss of accuracy, by exploiting the sample variance reduction due to the large difference in the time scale between events occurring in the application and in the packet layer.

Utsumi Shintaro, Takahashi Shingo, Ohori Kotaro, Anai Hirokazu. Agent-based analysis for design of signage systems in large-scale facilities // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.3134-3135.
This paper focuses on an airport terminal and develops an agent-based model that represents the behavioral characteristics of passengers and the essential features of signs. The simulation with the model can show possible passenger behaviors and congestion situations in the facility under many different types of signage systems. As the results, we can support the managers decision to build the signage system before it is actually implemented.

a href="http://simulation.su/uploads/files/default/2015-van-buuren-kommer-van-der-mei-bhulai.pdf" target="_blank">van Buuren Martin, Kommer Geert Jan, van der Mei Rob, Bhulai Sandjai. A simulation model for emergency medical services call centers // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.844-855.
This paper presents a detailed discrete event simulation model for emergency medical services (EMS) call centers. The model provides insight into the EMS call center processes and can be used to address strategic issues, such as capacity and workforce planning. We analyze results of the model that are based on real EMS call center data to illustrate the usefulness of the model.

Varela C.A.R., Velandia F.B., Rey M.A.M., Romero N.G., Neira N.O. (2015). Foraging Multi-Agent System Simulation Based on Attachment Theory // In ISCS 2014: Interdisciplinary Symposium on Complex Systems (pp. 359-364). Springer International Publishing.

Vasileva, S. Simulations of the implementation of primary copy two-phase locking in distributed database systems. // COMPUTER MODELLING & NEW TECHNOLOGIES 2015 19(4B) 17-23 link.

Vasileva, S. Some applications of the GPSS World Extended Editor to create of educative simulation models. // Journal of the Technical University Sofia, branch Plovdiv. «Fundamental Sciences and Applications», Vol. 21, Book 1, 2015, pp.215-220, (In Bulgaria).

Volovoi Vitali. Simulation with stochastic Petri-nets // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.88-102.
This tutorial reviews the role of Stochastic Petri Nets (SPNs) in stochastic simulation. The evolution of SPNs as a component-level state-space modeling framework is discussed. SPNs are compared to both process-based approaches to discrete event simulation and to agent-based modeling.

Wainer Gabriel. DEVS modelling and simulation for development of embedded systems // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.73-87.
We present a Model-driven framework to develop cyber-physical systems based on the DEVS (Discrete Event systems Specification) formalism. This approach combines the advantages of a simulation-based approach with the rigor of a formal methodology. We will discuss how to use this framework to incrementally develop embedded applications, and to seamlessly integrate simulation models with hardware components. Our approach does not impose any order in the deployment of the actual hardware components, providing flexibility to the overall process.

Wang C., Mao Y., Xiang Z., Zhou Y. Ship block logistics simulation based on discrete event simulation // iJOE, Volume 11, Issue 6, 2015. Pp.16-21.

Wang H., Mostafizi A., Cramer L.A., Cox D., Park H. (2015). An agent-based model of a multimodal near-field tsunami evacuation: Decision-making and life safety // Transportation Research Part C: Emerging Technologies.

Wang Y.N., Chen H. (2015). Scenario Simulation of Land Use Based on Net Logo Model—A Case Study for Matiwa Village of Mizhi County of Shaanxi Province // Journal of Anhui Agricultural Sciences, 25, 111.

Warnke Tom, Steiniger Alexander, Uhrmacher Adelinde M., Klabunde Anna, Willekens Frans. ML3: a language for compact modeling of linked lives in computational demography // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.2764-2775.

Weintrop D., Head B., Wilensky U. (2015). Plotting Programming Trajectories with the NetLogo Data Explorer // In Proceedings of Information Visualization, 2015. Chicago, IL. IEEE.

Wenzler F., Gunthner W.A. 2015. Ressourcen-beschränkte Terminplanung mit einem System kollaborativer Agenten // In Simulation in Production and Logistics 2015, M. Rabe and U. Clausen (Eds.). Fraunhofer, Stuttgart, pp.721–730.

White K. Preston, Ingalls Jr. Ricki G. Introduction to simulation // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.1741-1755.
Simulation is experimentation with a model. The behavior of the model imitates some salient aspect of the behavior of the system under study and the user experiments with the model to infer this behavior. This general framework has proven a powerful adjunct to learning, problem solving, and design. In this tutorial, we focus principally on discrete-event simulation—its underlying concepts, structure, and application.

Wilensky U., Rand W. (2015). An introduction to agent-based modeling: Modeling natural, social and engineered complex systems with NetLogo // Cambridge, MA: MIT Press.

Wilkerson-Jerde M. H., Wagh A., Wilensky U. (2015). Balancing curricular and pedagogical needs in computational construction kits: Lessons from the Delta Tick project // Science Education, 99(3), 465-499.

Williams Roy, Williams Scott, Das Amar. Using agent-based simulation to understand populatation dynamics and coevolution in host-pathogen relationships // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.3110-3111.

Wolf I., Schröder T., Neumann J., de Haan G. Changing minds about electric cars: An empirically grounded agent-based modeling approach // Technological Forecasting and Social Change. 2015. Vol. 94. P. 269-285.

Yan Chen, Yong-Hong Kuo, Hari Balasubramanian, Chaobai Wen. Using simulation to examine appointment overbooking schemes for a medical imaging center // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.1307-1318.
In this paper, we present an appointment scheduling problem faced by a medical imaging center in a major hospital in Macau. We developed an empirically calibrated simulation model to represent the appointment and medical diagnosis procedure as a multi-server queuing network with multiple patient classes. Four appointment overbooking schemes are proposed to compensate for patient no-shows and unpunctuality. Simulation results show that our proposed overbooking schemes significantly enhance the performance of the center.

Yanikara Fatma Selin, Kuhl Michael E. A simulation framework for the comparison of reverse logistic network configurations // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.979-990.
In this paper, we present a simulation framework for comparing alternative reverse logistic network configurations based on productivity and sustainability performance metrics. The resulting decision support tool enables the evaluation of user specified system and experimental parameters. An overview of the simulation framework is provided along with an example that illustrates the capabilities and functionality of the tool.

Yongchen G., Yang S., Jing M. (2015). A Study on the Multi-Agent Simulation of BBS Public Opinion Evolution Based on the Theory of Opinion Leaders // Journal of Intelligence, 2, 003.

Zandi M. (2015). Simulation of Ascorbic Acid Release from Alginate-Whey Protein Concentrates Microspheres at the Simulated Gastrointestinal Condition Using Netlogo Platform // Journal of Food Process Engineering.

Zandi M., Mohebbi M. (2015). An agen-based simulation of a release process for encapsulated flavour using the NetLogo platform // Flavour and Fragrance Journal, 30(3), 224-229.

Zehe Daniel, Cai Wentong, Knoll Alois, Aydt Heiko. Tutorial on a modeling and simulation cloud service // Proceedings of the 2015 Winter Simulation Conference L. Yilmaz, W. K V. Chan, I. Moon, T. M. K. Roeder, C. Macal, and M. D. Rossetti, eds.. – 2015. Huntington Beach, California, USA. – P.103-114.
In this tutorial we will present an approach of how to work with an entirely cloud-based solution for modeling and simulation, with an exemplary implementation of an urban traffic simulation cloud service. Since the computational offload from the workstation to a remote computing entity also allows the use of novel user interfaces (design and devices), through the use of RESTful interfaces, use-case applicable interfaces for simulations can also be created.

Zhang J.; Tong L.; Lamberson P.J.; Durazo-Arvizu R.A.; Luke A.; Shoham D.A. (2015). Leveraging social influence to address overweight and obesity using agent-based models: The role of adolescent social networks // Social Science & Medicine. Elsevier BV. 125: 203–213. doi:10.1016/j.socscimed.2014.05.049.