Статьи 2019 года (I...O)



Ilyinsky A., Goroshnikova T. (2019, October). Navigation in NSR as large-scale system: Ship path analysis in non-severe ice condition // In 2019 Twelfth International Conference Management of large-scale system development (MLSD) (pp. 1-4). IEEE.

Jain S., Narayanan A., Lee Y.-T.T. Infrastructure for model based analytics for manufacturing // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.2037-2048.
This paper proposes a shared infrastructure for virtual factory model based analytics that can be employed by small and medium enterprises.

Jaxa-Rozen M., Kwakkel H.J, Bloemendal M. (2019) A coupled simulation architecture for agent-based/geohydrological modelling with NetLogo and MODFLOW // Environmental Modelling and Software 115 (2019) 19-37.
This work introduces a Python-based software architecture which couples the NetLogo agent-based platform with the MODFLOW/SEAWAT geohydrological modelling environment. This approach enables users to design agent-based models in NetLogo's user-friendly platform, while benefiting from the full capabilities of MODFLOW/SEAWAT. This workflow is illustrated for a simplified application of Aquifer Thermal Energy Storage.

Jones W., Kotiadis K., O_Hanley J. Engaging stakeholders to extend the lifecycle of hybrid simulation models // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.1304-1315.

Jones K., Munoz B., Rineer J., Bobashev G., Hilscher R., Rhea S. On calibrating a microsimulation of patient movement through ahealthcare network // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.205-214.
Hospital admission and discharge dynamics facilitate pathogen transmission among individuals in communities, hospitals, nursing homes, and other healthcare facilities. We developed a microsimulation to simulate this movement, as patients are at increased risk for healthcare-associated infections, antibiotic exposure, and other health complications while admitted to healthcare facilities.

Juan A.A., Panadero J., Reyes-Rubiano L., Faulin J., de la Torre R., Latorre I. Simulation-based optimization in transportation and logistics: comparing sample average approximation with simheuristics // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.1906-1917.
This paper reviews some recent applications of Simulation-based optimization (SBO) in the area of transportation and logistics. This paper presents the stochastic variants for the team orienteering problem to show the application of the SBO solving methods.

Kabeer M., Riaz F., Jabbar S., Aloqaily M., Abid S. (2019, June). Real World Modeling and design of Novel Simulator for affective computing inspired autonomous vehicle // In 2019 15th International Wireless Communications & Mobile Computing Conference (IWCMC) (pp. 1923-1928). IEEE.

Kamhuber F., Sobottka T., Heinzl B., Sihn W. An efficient multi-objective hybrid simheuristic approach for advanced rolling horizon production planning // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.2108-2118.

Kamimura K., Gardiner B., Dupont S., Finnigan J. (2019) Agent-based modelling of wind damage proceses and patterns in forests // Journal «Agricultural and Forest Meteorology», 268 (2019), pp. 279-288.
Powerful storms, consisting of strong gusts and winds, damage forests. Therefore, foresters need forest management strategies to reduce the damage risk. This paper focused on the damage patterns within the forest as the final results of multiple tree-wind dynamic interactions in time and space during a storm.

Kapat S.K., Tripathy S.N. (2019). Malware architectural view with performance analysis in Network at its activation state // In Cognitive Informatics and Soft Computing (pp. 207-216). Springer, Singapore.

Keskin M., Akhavan-Tabatabaei R., Catay B. Electric vehicle routing problem with time windows and stochastic waiting times at recharging stations // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.1649-1659.

Kesler G., Lucas T.W., Sanchez P.J. A data farming analysis of a simulation of armstrong’s stochastic salvo model // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.2443-2454.

Kim T., Morrison J.R. A numerical study on the structure of optimal preventive maintenance policies in prototype tandem queues // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.2281-2291.

Kim H.-O., Park S.-H., Park J.Y., Morrison J.R. On the consequences of un-modeled dynamics to the optimality of schedules in clustered photolithography tools // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.2224-2235.

Kopp D., Monch L. Fast heuristics for making qualification management decisions in wafer fabs // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.2348-2359.

Koralewski T.E., Westbrook J.K., Grant W.E., Wang H.H. (2019). Coupling general physical environmental process models with specific question-driven ecological simulation models // Ecological modelling, 405, 102-105.

Kostylenko O., Rodrigues H., Torres D. (2019) The spread of a financial virus through Europe and beyond // AIMS Mathematics, Volume 4, Issue 1, pp.86-98.

Krahl D., Milburn-Pyle D. Use of a combined discrete rate and population balance simulation for the design and optimization of a high shear agglomeration process // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.1340-1351.
The application of a hybrid discrete rate and population balance simulation model to a high shear agglomeration process provides in-depth and dynamic insight into how a non-homogeneous product behaves across the entire process in addition to the individual process component level. By tracking individual product attributes throughout the process, the customer can size equipment, design control systems, and optimize process parameters, while reducing engineering development time and cost.

Kunc M. Strategic planning: the role of hybrid modelling // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.1280-1291.
Strategic planning using simulation is an increasing field of practice mostly driven by the big consulting firms. While System Dynamics is a widely used simulation method in strategic planning given its advantage on global aggregates and deterministic model, hybrid modelling can achieve similar popularity. This paper presents some suggestions on how to use hybrid modelling in strategic planning.

Lahav O., Hagab N., Levy S.T., Talis V. (2019). Computer-model-based audio and its influence on science learning by people who are blind // Interactive Learning Environments, 27(5-6), 856-868.

Lam H., Qian H. Validating optimization with uncertain constraints // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.3621-3632.
We consider optimization with uncertain or probabilistic constraints under the availability of limited data or Monte Carlo samples. In this situation, the obtained solutions are subject to statistical noises that affect both the feasibility and the objective performance.

Lamghari-Idrissi D., Soellaart D., Basten R., Dellaert N. Influence of spare parts service measures on the performance of front-end wafer production process // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.2269-2280.

Law A.M. How to build valid and credible simulation models // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.1402-1414.
In this tutorial we present techniques for building valid and credible simulation models. We will also discuss the difficulty in using formal statistical techniques (e.g., confidence intervals) to validate simulation models.

Lazarova-Molnar S., Li X. Deriving simulation models from data: steps of simulation studies revisited // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.2771-2782.
In this paper we explore the idea of derivation of simulation models from data.

Lee J.-H., Kim Y., Kim Y.B., Kim H.-J., Kim B.-H., Chung G.-H. A sequential search framework for selecting weights of dispatching rules in manufacturing systems // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.2201-2211.

Lee W.-J., Kim B.-H., Ko K., Shin H. Simulation based multi-objective fab scheduling by using reinforcement learning // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.2236-2247.
In this paper, we formulate the fab scheduling problem as a semi-Markov decision process and propose a reinforcement learning method used in conjunction with the fab simulator to obtain the (near-)optimal dispatching policy.

Li D., Smith J.S., Li Y. Coordinated control of multi-zone avs/rs, conveyors and pick-up operations in warehouse system // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.2049-2060.
This paper focuses on the control strategies for coordinating the subsystem operations with regard to the conveyor system, rack storage system and pick-up system in order to maximize the system’s throughput capacity and minimize the storage/retrieval times of items in an e-commerce picking warehouse.

Li H., Peng Y., Xu X., Chen C.-H., Heidergott B.F. Dynamic sampling procedure for decomposable random networks // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.3752-3763.
This research studies the problem of node ranking in a random network. Specifically, we consider a Markov chain with several ergodic classes and unknown transition probabilities which can be estimated by sampling.

Li J. (2019, October). Simulation research on marketing effect of enterprise in social network based on SIR model // In 4th International Conference on Modern Management, Education Technology and Social Science (MMETSS 2019). Atlantis Press.

Li Y., Ji W. Enhanced input modeling for construction simulation using bayesian deep neural networks // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.2978-2985.
This paper aims to propose a novel deep learning-integrated framework for deriving reliable simulation input models through incorporating multi-source information.

Li Y., Xu S., Wu L., AbouRizk S., Kwon T.J., Lei Z. A generic simulation model for selecting fleet size in snow plowing operations // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.2966-2977.

Line Have Musaeus P.M., Musaeus P. (2019).Computational Thinking in the Danish High School: Learning Coding, Modeling, and Content Knowledge with NetLogo // Proceedings of the SIGCSE '19 Proceedings of the 50th ACM Technical Symposium on Computer Science Education (pp. 913-918). Minneapolis, MN, USA.

Lippe M., Bithell M., Gotts N. Natalie D., Barbrook P., Giupponi C., Hallier M., Hofsted G., Le Page C., Matthews R., Schluter M., Smith P., Teglio A,, Thellman K. (2019). Using agent-based modelling to simulate social-ecological systems across scales // GeoInformatica 23.2, 269-298.

Liu G., Ye J., Argyres C. (2019). Modeling and simulation of the knowledge growth process among new energy technology firms in the distributed innovation network // DYNA-Ingeniería e Industria, 95(1).

Liu W., Li H., Lee L.H., Chew E.P., Xiao H. Optimal computing budget allocation for binary classification with noisy labels and its applications on simulation analytics // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.3587-3696.
In this study, we consider the budget allocation problem for binary classification with noisy labels. The classification accuracy can be improved by reducing the label noises which can be achieved by observing multiple independent observations of the labels.

Liu X., Jin D., Zhang T. A parallel simulation platform for train communication networks // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.2819-2830.

Liu Y., Li F. & Su Y. (2019) Critical Factors Influencing the Evolution of Companies’ Environmental Behavior: An Agent-Based Computational Economic Approach SAGE Open.

Liu Z., Li X., Khojandi A., Lazarova-Molnar S. On the extension of schelling’s segregation model // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.285-296.
In this paper, we first adopt Agent-Based Modelingto reconstruct Schelling’s original model and discuss its convergence behaviors under different threshold levels. Then, we extend Schelling’s model with multidimensional agents and investigate convergence behaviors of the model.

Loper M.L. Simulation trust and the Internet of Things // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.2-16.
This paper looks at trust from an IoT perspective, describing a set of research projects conducted that span multiple dimensions of trust, and discusses whether these concepts of trust apply to simulation.

Lopez E.C., Marmier F., Fontanili F. Bus fleet size dimensioning in an international airport using discrete event simulation // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.464-475.

Luanda A. (2019, June). A Gift-Exchange Model for the maintenance of group cohesion in a telecommunications scenario // In Distributed Computing and Artificial Intelligence, 16th International Conference (Vol. 1003, p. 189). Springer.

Lueck J., Rife J.H., Swarup S., Uddin N. Who goes there? Using an agent-based simulation for tracking population movement // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.227-238.
We present a method to apply simulations to the tracking of a live event such as an evacuation. We assume only a limited amount of information is available as the event is ongoing, through population-counting sensors such as surveillance cameras.

Lugaresi G., Travaglini D., Mattaryland A. A LEGO manufacturing system as demonstrator for a real-time simulation proof of concept // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.2025-2036.
The goal of this work is to prove the applicability of a Real-Time Simulation framework that prescribes to exchange current-status data from a manufacturing system and to run alternative simulation models to decide the next moves.

Mahfouz A., Allen D., Arisha A., Elbert R., Gleser M. A post-brexit transportation scenario analysis for an agri-fresh produce supply chain // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.1789-1800.
This paper gives a first indication on how Agri-Fresh Produce Supply Chains forwarders in Ireland can deal with a no-deal Brexit situation.

Maızi Y., Zhu E.(C.), Wu T., Zhou J. A reliable deployment strategy for public electric vehicle charging stations: a discrete event simulation model for power grid and traffic networks // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.1660-1671.
In this paper, we aim to develop a framework to establish a reliable urban public charging infrastructure. We first determine the optimal locations and size of those stations by a robust optimization model incorporating uncertain traffic flows and existing power grid networks; and then we use a discrete event simulation approach to model more realistic charging demands.

Malaina A. (2019) The Paradigm of Complexity in Sociology: Epistemological and Methodological Implications, Complexity Applications // Language and Communication Sciences, 31-42.

Manda A.B., Uzsoy R. Optimzing engineering and production lots during product transitions in semiconductor manufacturing // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.2291-2303.

Manriquez M., Loor F. Gil-Costa V., Marin M. A digital TV-based distributed image processing platform for natural disasters // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.2689-2700.

Martin K., Horn M., Wilensky U. (2019). Prevalence of direct and emergent schema and change after play // Informatics in Education, 18(1), 183-212.

Mayes R. (2019). Quantitative reasoning and its role in interdisciplinarity // In Interdisciplinary mathematics education (pp. 113-133). Springer, Cham.

McEligot K., Brouse P., Crooks A. Sea bright, new jersey reconstructed: agent-based protection theory model responses to hurricane sandy // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.251-262.
This paper discusses the complexity of the Protective Action Decision Model and Protection Motivation Theory for human decision making regarding hazard mitigations.

McNulty M., Smith J.D., Villamar J., Burnett-Zeigler I., Vermeer W., Benbow N., Gallo C., Wilensky U., Hjorth A., Mustanski B., Schneider C., Brown H. (2019). Implementation Research Methodologies for Achieving Scientific Equity and Health Equity // Ethnicity & Disease, 29(1), 83-92.

Mehdi N., Starly B. A simulator testbed for MT-Connect based machines in a scalable and federated multi-enterprise environment // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.2178-2189.
This paper introduces a flexible simulator testbed of multiple MTConnect agents and adapters for simulating Levels 0 & 1 of the ISA-95 framework and help support R&D activities in complex multi-enterprise supply chain scenarios.

Meibner M., Rehtanz C., Myrzik J. Application of the non-linear optimization algorithm differential evolution for optimization of manufacturing systems regarding their energy efficiency // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.2154-2165.

Mes M.R.K., Koot M. Simulation solution validation for an integrated emergency post // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.1160-1171.

Mesabbah M., Abo-Hamad W., McKeever S. A hybrid process mining framework for automated simulation modelling for healthcare // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.1091-1102.
This paper presents an extension of the Auto Simulation Model Builder framework previously developed by authors adopted for healthcare systems.

Mielczarek B. Combining simulation techniques to understand demographic dynamics and forecast hospital demands // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.1114-1125.
The population model was constructed as a system dynamics model while patient pathways were modeled using a discrete event approach. Results showed that the hybrid model enabled analyses and insights that were not delivered by each sole method.

Mieth C. Semantic enrichment of spatio-temporal production data to determine lead times for manufacturing simulation // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.2061-2072.
This paper investigates how historical position data can be used for the determination of lead times and respective time shares.

Milde M., Reinhart G. Automated model development and parametrization of material flow simulations // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.2166-2177.
In this paper we present a new approach to automate time-consuming steps in simulation projects. Based on general tracking and tracing data, our approach reduces the efforts in the area of data acquisition and automates the steps of model development, model parameterization and model implementation.

Milne R. J., Delcea C., Cotfas L.A., Salari M. (2019). New methods for two-door airplane boarding using apron buses // Journal of Air Transport Management, 80, 101705.

Mittal S., Tolk A., Pyles A., Van Balen N., Bergollo K. Digital twin modeling, co-simulation and cyber use-case inclusion methodology for IoT systems // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.2653-2664.
This paper will present a digital twin engineering methodology as applicable to IoT device Test & Evaluationand cyber experimentation.

Mizuta H. Jam tail estimation using vehicle and road agents // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.1965-1976.

Moreira P.C.M., Leite R.P., Silva V.A. Evaluation of risk and efficiency impacts on offshore diesel logistics of different operational processes through discrete-event simulation // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.1941-1952.

Mousavi B.A., Azzouz R., Heavey C., Ehm H. Simulation-based analysis of the nervousness within semiconductors supply chain planning: insight from a case study // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.2073-2084.

Muller M., Schmidt S., Reggelin T. Deadlock and collision handling for automated rail-based storage and retrieval units // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.1591-1601.
When planning logistics systems with multiple transport objects or systems, modeling requires the implementation of complex control logic to avoid collisions and deadlocks. This paper illustrates a procedure for the development of such control logic on the example of rail-based storage and retrieval units in combinations with lifts in the picking area of an industrial laundry.

Murali A.K., Liu E., Allen T.T. Discrete event simulation of cyber maintenance policies according to nested birth and death processes // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.774-785.
This article proposes a novel discrete event simulation model for predicting cyber maintenance costs under multiple scenarios. In this study, our model of the evolution of computer hosts is similar to the Susceptible-Infected-Removed epidemiological model.

Muraru A., Lile R., Boșcoianu E.C., Boșcoianu M., Vladareanu L. (2019). The UAV control approach by using multi agent systems // Periodicals of Engineering and Natural Science, vol.7, no.1.

Musaeus L.H., Musaeus P. (2019, February). Computational thinking in the Danish high school: learning coding, modeling, and content knowledge with NetLogo // In Proceedings of the 50th ACM Technical Symposium on Computer Science Education (pp. 913-919).

Naderlinger A. Harnessing concurrency in synchronous block diagrams to parallelize simulation on multi-core hosts // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.702-713.
We present an execution mechanism that harnesses multi-core hosts for accelerating individual simulation runs through parallelization. The approach is based on a model transformation.

Nataraja B.M., Atan Z. Simulation of allocation policies for a serial inventory system under advance demand information // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.1871-1882.
In this paper, we simulate allocation policies for a two-stage inventory system that receives perfect advance demand information from customers belonging to different demand classes.

Ng H., Othman W., Bakar E., Mat Noor N., Hawary A. (2019). Meerkats behavior modelling using NetLogo // Robotika, 1(1), 16-21.

Ninh A., LeFew M., Anisimov V. Clinical trial simulation: modeling and practical considerations // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.118-132.

Nutaro J., Ozmen O. Using simulation to quantify the reliability of control software // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.3267-3276.

Onder S.T., Balci O. Architecture and design of a cloud-based visual simulation environment // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.2737-2748.

Onggo B.S., Juan A.A., Panadero J., Corlu C.G., Agustin A. An inventory-routing problem with stochastic demand and stock-out: a solution and risk analysis using simheuristics // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.1977-1988.
This paper considers an example of a complex supply chain operation that can be viewed as an Inventory-Routing Problem with stochastic demands.

Onggo B.S., Yilmaz L., Klugl F., Terano T., Macal C.M. Credible agent-based simulation – an illusion or only a step away? // Proceedings of the 2019 Winter Simulation Conference N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, and Y.-J. Son, eds. 2019. Maryland, USA. P.273-284.
This paper presents the perspective of three academic panelists and a practitioner on the credibility of Agent-based Simulation (ABS). The discussion reveals that the increasing use of ABS models to explain social phenomena or systems that exhibit emergent behavior pose a challenge for model credibility.

Opiyo N.N. (2019). Impacts of neighbourhood influence on social acceptance of small solar home systems in rural western Kenya // Energy Research & Social Science, 52, 91-98.

Owusu P.A., Leonenko V N., Mamchik N.A., Skorb E.V. (2019). Modeling the growth of dendritic electroless silver colonies using hexagonal cellular automata // Procedia Computer Science, 156, 43-48.

Ozawa S., Haynie D., Bessias S., Laing S., Ladi E. (2019) Modeling the Economic Impact of Substandard and Ffalsified Antimalarials in the Democratic Republic of the Congo // The American Journal of Tropical Medicine and Hygiene.





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