Ahrweiler P., Pyka A., Gilbert N. (2011). An implementation of the pathway analysis through habitat (PATH) algorithm using NetLogo // The Journal of Product Innovation Management, 28(2).

Akopov A.S. (2011) About the question of realization of econometrics models on the web-server with multi-user access support // Business Informatics, № 2, 2011. pp. 3–11.

Aksyonov K.A., Bykov E.A., Antonova A.S., Aksyonova O.P., Sufrygina E.M., Goncharova N.V. Tools and methodologies for business processes formalization: application to multi-agent systems // Proceedings of the 5th European Symposium on Computer Modeling and Simulation. 2011. P. 113–118.

Aksyonov K.A., Bykov E.A., Smoliy E.F., Sufrygina E.M., Sheklein A.A., Aksyonova O.P. and others. Efficient Decision Support with Simulation-Based System BPsim.DSS: Advanced Simulation Techniques. ISMS, 2011 Second International Conference on Intelligent Systems, Modelling and Simulation, Phnom Penh, Cambodia, 2011. p. 30-34.
Эффективное принятие решений в системе, основанной на имитационном моделировании BPsim.DSS: передовая техника имитационного моделирования.

Alfaro J.F., Miller S.A. (2011). Planning the development of electricity grids in developing countries: An initial approach using Agent Based Models // Proceedings of 2011 IEEE International Symposium on Sustainable Systems and Technology (ISSST), May 16-18, 2011, Chicago, IL, 1-6.
This paper presents a proof of concept model for the electrification process of developing countries. Considering the general needs and characteristics in those countries is important as they share factors far from the developed world situation. However, enough flexibility is included to allow implementation in individual countries with unique circumstances.

Antonova G.M. Application of Pattern Recognition Methods to Solve Optimization Problems Using Imitation Models // PRIA (DOI 10.134/S 1054661811020076), Volume 21, № 2, 2011, p.113-116.

Antonova G.M. Optimization-Simulation with Continuous Criteria Using // Conference Proceedings. 18th World Congress of International Federation of Automatic Control. IFAC’11 (August 27-September 03, 2011), Milano, Italy, 2011, p.5543-5548.

Arnould G., Khadraoui D., Armendariz M., Burguillo J.C., Peleteiro A. (2011). A transport based clearing system for dynamic carpooling business services // Proceedings of 2011 11th International Conference on ITS Telecommunications (ITST), 23-25 Aug. 2011, pp. 527-533.

Artel A., Teymour F., North M.J., Cinar A.: A multi-agent approach using perceptron-based learning for robust operation of distributed chemical reactor networks // Int Sci J Eng App Artif Intell, 2011, 24:1035-1045.

Asman B.C., Kim M.H., Moschitto R.A., Stauffer J.C., Huddleston S.H. (2011). Methodology for analyzing the compromise of a deployed tactical network // Proceedings of the 2011 Systems and Information Engineering Design Symposium (SIEDS), April 29, 2011, pp. 164-169.

Osman Balci How to Successfully Conduct Large-Scale Modeling and Simulation Projects // In Proceedings of the 2011 Winter Simulation Conference (Phoenix, AZ, Dec. 11-14). IEEE, Piscataway, NJ, 2011. P. 176-182.

Ballinas-Hernandez A.L., Munoz Melendez A., Rangel-Huerta A. (2011). Multiagent System Applied to the Modeling and Simulation of Pedestrian Traffic in Counterflow // Journal of Artificial Societies and Social Simulation (JASSS), 14 (3) 2. (June 2011) .

Baracaldo N., Lopez C., Anwar M., Lewis M. (2011). Simulating the Effect of Privacy Concerns in Online Social Networks // Proceedings of the IEEE International Conference on Information Reuse and Integration, IRI 2011, 3-5 August 2011, Las Vegas, Nevada, USA 2011.

Barbosa J., Leitao P. (2011). Simulation of Multi-agent Manufacturing Systems using Agent-based Modelling Platforms // Proceedings of the 2011 9th IEEE International Conference on Industrial Informatics (INDIN), 26-29 July 2011, pp. 477-482.
This paper discusses the simulation of agent-based manufacturing systems and introduces the advantages of using Agent-Based Modelling tools. The NetLogo platform is used to illustrate the benefits of such tools in the manufacturing world on the specification of a Multi-agent systems system for a washing machine production line.

Bida M., Brom C., Popelova M. (2011). To date or not to date? A Minimalist affect-modulated control architecture for dating virtual characters // Lecture Notes in Computer Science, 6895(2011): 419-425.

Bondarevsky A.S., Lebedev A.V. Simulation modeling: definition, applicability and technical realization // Fundamental research, №12, 2011, p.535-541.
All technically implemented and almost significant operations of modeling have seven variety. From this variety of modeling three are imitating. At the heart of resulted definition of imitating modeling lies evident (having physical sense) an aspect of coordinates and parametres of its images-models. It is a consequence of detailed elaboration of coordinates and parametres of imitating models. It is thus gained that at imitating modeling five properties occur. In this connection, for example, it is gained that imitating modeling appears the unique means of realisation of coordinate-parametrical management of difficult installations.

Borri D., Camarda D. Planning for the environmental quality of urban microclimate: a multi-agent-based approach // Lecture Notes in Computer Science. 2011. Vol. 6874. P. 129-136.

Braga D.S., Alves F.O.M., Lima Neto F.B., Menezes L.C.S. (2011). AspectNetLogo: Uma Proposta de Linguaguem Orientada a Aspectos para a Modelagem de Sistemas Multi-Agentes em Simulacoes Sociais // In: X Congresso Brasileiro de Inteligencia Computacional, 2011. Fortaleza, CE. Sessao Tecnica 28 (Interfaces e Ferramentas).

Brailsford, S.C., Silverman, E., Rossiter, S., Bijak, J., Shaw, R., Viana J., Noble, J. Efstathiou S. and Vlachantoni A. 2011. Complex systems modeling for supply and demand in health and social care. Proceedings of the 2011 Winter Simulation Conference, Phoenix, Az. S. Jain, R.R. Creasey, J. Himmelspach, K.P. White, and M. Fu, eds.

Braun A., Rosner H.-J. (2011). Disturbance and succession. Potential of agent-based systems for modeling vulnerable ecosystems. Application to land degradation processes // In Car, A. / Griesebner, G. / Strobl, J. (Eds.) Geospatial Crossroads @ GI_Forum '11. Proceedings of the Geoinformatics Forum Salzburg, pp. 12-21.

Brito, T.B., E.F.C. Trevisan, and R.C. Botter. 2011. A Conceptual comparison between discrete and continuous simulation to motivate the hybrid simulation technology // In Proceedings of the 2011 Winter Simulation Conference, edited by S. Jain, R.R. Creasey, J. Himmelspach, K.P. White, and M. Fu, 3915-3927. Piscataway, New Jersey: Institute of Electrical and Electronics Engineers, Inc.

Petr Cernohorsk, Jan Voracek Computational Modeling in Strategic Marketing // International Scholarly and Scientific Research & Innovation 5(12) 2011. P.564-572.

Cetinkaya D., Verbraeck A. Metamodeling and model transformations in modeling and simulation // Proceedings of the 2011 Winter Simulation Conference, 2011, pp.3048-3058.

Chen Zixia, Jiang Changbing. Simulation of a Flexible Manufacturing System with AutoMod Software // Intelligent Information Management, 2011, 3, 186-189.

Cheng, Ch. H., Chan, K. Y. D. Simulation optimization of part input sequence in a flexible manufacturing system // In Proceedings of the 2011 Winter Simulation Conference, IEEE, Inc., Tucson, AZ, USA, pp. 2374–2382.

Collard P., Mesmoudi S. (2011). How to Prevent Intolerant Agents from High Segregation? // Advances in Artificial Life, ECAL 2011: Proceedings of the Eleventh European Conference on the Synthesis and Simulation of Living Systems, T. Lenaerts, M. Giacobini, H. Bersini, P. Bourgine, M. Dorigo and R Doursat. MIT Press, (ISBN 978-0-262-29714-1). 2011.

Cui Y., Martin U. (2011) Multi-scale simulation in railway planning and operation // PROMET – Traffic & Transportation, 23(6), 511-517. Available: https://hrcak.srce.hr/file/122067.

Damaceanu R-C. (2011). Agent-based Computational Social Sciences using NetLogo // LAP LAMBERT Academic Publishing.

Damaceanu R-C. (2011). An Agent-based Computational Study of Wealth Distribution in Function of Technological Progress Using NetLogo // American Journal of Economics, Vol 1.1, pg. 15-20.

de Bakker G., van Bruggen J., Jochems W., Sloep P.B. (2011). Introducing the SAPS System and a corresponding allocation mechanism for synchronous online reciprocal peer support activities // Journal of Artificial Societies and Social Simulation (JASSS).14 (1).

Dermody J.; Tanner C. & Jackson A. (2011). The Evolutionary Pathway to Obligate Scavenging in Gyps Vultures // PLoS ONE 6(9): e24635.

Dickerson M. (2011). Multi-agent simulation and NetLogo in the introductory computer science surriculum // Journal of Computing Sciences in Colleges, 27(1).
The tutorial introduces the NetLogo programming language and presents an approach to an introductory computer science course based on multi-agent simulation and NetLogo.

Dixon D.S. (2011). Preliminary results from as agent-based adaptation of friendship games // 86th Annual Conference of Western Economics.
This paper presents agent-based model equivalents of friendship based games and compares the results with the theoretical models.

Eskandari, H., Mahmoodi, E., Fallah, H., Geiger, D. Ch. Performance analysis of commercial simulation-based optimization packages: OptQuest and Witness Optimizer // In Proceedings of the 2011 Winter Simulation Conference, IEEE, Inc., Tucson, AZ, USA, pp. 2363–2373.

Fekir A., Benamrane N. (2011). Segmentation of medical image sequence by parallel active contour // Advances in Experimental Medicine and Biology, 696(6): 515-522.

Filho H.S.B., de Lima Neto F.B., Fusco W. (2011). Migration and Social Networks – An Explanatory Multi-evolutionary Agent-Based Model // Proceedings of the 2011 IEEE Symposium on Intelligent Agent (IA), 11-15 April 2011, pp. 1-7.
In this paper we propose a new multi-evolutionary agent model dedicated to social simulations, mainly for those problems where higher order dynamic behaviors (e.g. secondary emergent phenomena) are important to the investigated phenomenon. Its usefulness lies on its multilevel evolutionary adaptability which enables it to capture multiple parallel phenomena.

Fonseca P. (2011). Simulation hypotheses. In: International Conference on Advances in System Simulation. Third International Conference on Advances in System Simulation. Barcelona: 2011, pp.1-6.

Frank B.M., Piccolo J.J., Baret P.V. (2011). A review of ecological models for brown trout: towards a new demogenetic model // Ecology of Freshwater Fish 20(2), pp. 167-198.

Frias-Martinez E., Williamson G., Frias-Martinez V. An agent-based model of epidemic spread using human mobility and social network information. In: Proceedings of the 3rd International Conference on Social Computing (SocialCom’11), Boston, MA, USA, 9–11 October 2011. Pp. 49–56. DOI: 10.1109/PASSAT/ SocialCom.2011.142.

Gabbreillini S. (2011). Simulare meccanismi sociali con NetLogo: Una introduzione // Methodology and Techniques of Social Research. E-book.

Gasselberg M.A., Sinelshchikov A.V. The application of simulation modeling for the analysis of the efficiency of grain transfer processes // Вестник АГТУ, № 2 (52), ISSN 1812-9498 / Астрахань, 2011, c.31-35.
The problem of the efficiency of grain terminals in the ports of the Russian Federation is covered. The actuality of the problem of the developing of proposals, concerning the competitive recovery of Caspian ports, is justified. The application of simulation modeling as an investigation technique to the researches of complex production systems, which can be considered as a contributory factor for the set-up problem, is justified.

Andrea Gavulová, Marek Drličiak Microsimulation using for capacity analysis of roundabouts in real conditions // Proceedings of the 11th International Conference «Reliability and Statistics in Transportation and Communication» (RelStat’11), 19–22 October 2011, Riga, Latvia, p. 226-233. ISBN 978-9984-818-46-7.
The article deals with creation and calibration of microscopic traffic models and with the mentioned comparing of results.

Gobert J., O'Dwyer L., Horwitz P., Buckley B., Levy S.T., Wilensky U. (2011). Examining the relationship between students' epistemologies of models and conceptual learning in three science domains: Biology, Physics, & Chemistry // International Journal of Science Education, 33(5), 653-684.

Gui-sheng Y., Ji-jie W., Hong-bin D., Jia L. (2011). Intelligent Viral Marketing algorithm over online social network // Proceedings of 2011 Second International Conference on Networking and Distributed Computing (ICNDC), 21-24 Sept. 2011, pp. 319-323.
This paper attacks the problem successfully by implementing intelligent algorithms such as GA, DE, PSO. Considering of the huge search space, we sharply decrease the scalability of the network through analyzing the datasets and sampling the data according to a power law property. Experiment results showed that the model wemdesigned for solving viral marketing problem outperform other current search methods.

Hussain T., Al-Mutib K.N., Alghamdi A.S. (2011). Towards software engineering process for C4I systems // Proceedings of the 2011 IEEE 3rd International Conference on Communication Software and Networks (ICCSN), 27-29 May 2011, pp. 125-129.
This paper highlights the distinguished characteristics and operational requirements of Command Control, Communication Computer and Intelligence systems which poses challenges to SwE process and practices. This paper also discuss the possible future research areas in order to enhance SwE process so that better software could drive these complex systems as required.

Kim J-W., Hanneman R.A. (2011). A Computational Model of Worker Protest // Journal of Artificial Societies and Social Simulation (JASSS), 14 (3) 1. (June 2011).

Kokorin S.V., Sokolov B.V., Ryzhikov Yu.I. Model And Algorithm For Combinational Optimization Of Information System Bandwidth // Proceedings 25th European Conference on Modelling and Simulation ECMS-2011, Digitaldruck Pirrot GmbH, 2011, 166-171.

Kopytov, E., Muravjov, A. Simulation of inventory control system for supply chain «producer – wholesaler – client» in ExtendSim environment // In Proceedings of the 25th European Conference on Modelling and Simulation (ECMS-2011), Krakow, Poland, June 3–4, 2011 (pp. 580–586).

Koroleva N.V. Conceptual bases of modeling direction of tourism development in recreational areas under market economy // ОБЩЕСТВО: ПОЛИТИКА, ЭКОНОМИКА, ПРАВО. 2011, № 2. З. 110-116.
The article represents the author's approach to the conceptual bases of modeling direction of tourism development in recreational areas. The purpose and main tasks of the modeling are determined, the classification of mathematic models is represented, the significance and the main challenges imitating modeling are stressed.

Kotenko I., Konovalov A., Shorov A. Simulation of botnets and protection mechanisms against them: software environment and experiments // 16th Nordic Conference on Secure IT-Systems. October 26th-28th, 2011, Tallinn, Estonia, Preproceedings, Cybernetica, 2011. p.119-126.

Kottonau J. (2011). An interactive computer model for improved student understanding of random particle motion and osmosis // Journal of Chemical Education, 88(6), pp.772-775.

Kumarappan S. (2011). Spatial pricing patterns of cellulosic biomass under oligopsony - A multi-agent simulation model // Paper presented at the 2011 AAEA & NAREA Joint Annual Meeting.

Kurve A., Kesidis G. (2011). Sybil Detection via Distributed Sparse Cut Monitoring // Proceedings of the 2011 IEEE international Conference on Communications (ICC), 5-9 June 2011.

Lamy F., Bossomaier T., Perez P. (2011). SimUse: Simulation of recreational poly-drug use // Proceedings of the 2011 IEEE Symposium on Artificial Life (ALIFE), 11-15 April 2011, pp. 170-177.
This on-going project aims to build an ontological model concerning recreational poly-drug use and to use an agent-based simulation, SimUse, to test and verify related public policies. We consider drug-use (and even more so poly-drug use) to be a complex adaptive system that needs to be studied via a methodology able.

Lamy F., Perez P., Ritter A., Livingston M. (2011). SimARC: An ontology-driven behavioural model of alcohol abuse // Proceedings of the Third International Conference on Advances in System Simulation, Oct. 23-29, pp. 128-133.
This paper describes an agentbased simulation model, called SimARC (Simulation of Alcohol-Related Consequences), aiming at exploring the complex interplay of these factors following a generative process whereby theory and model co-evolve within iterative loops.

Averill M. Law How the ExpertFit distribution-fitting software can make your simulation models more valid // Proceedings of the 2011 Winter Simulation Conference S. Jain, R.R. Creasey, J. Himmelspach, K.P. White, and M. Fu, eds. P.63-69.
In this paper, we discuss the critical role of simulation input modeling in a successful simulation study. Two pitfalls in simulation input modeling are then presented and we explain how any analyst, regardless of their knowledge of statistics, can easily avoid these pitfalls through the use of the ExpertFit distribution fitting software. We use a set of real-world data to demonstrate how the software automatically specifies and ranks probability distributions, and then tells the analyst whether the “best” candidate distribution is actually a good representation of the data. If no distribution provides a good fit, then ExpertFit can define an empirical distribution. In either case, the selected distribution is put into the proper format for direct input to the analyst’s simulation software.

Lektauers A., Trusins J., Trusina I. Combined multi-scale system dynamics and agent-based framework for sustainable community modelling // Sci. Journ. of Riga Technical Uni. Sustainable Spatial Development. 2011. vol. 2. pp. 23-29.

Levy S.T., Wilensky U. (2011). Mining students inquiry actions for understanding of complex systems // ScienceDirect Alert: Computers & Education, Vol. 56, Iss. 3, 2011. pp. 556-573.

Liu, J., Li, Ch., Yang, F., Wan, H. Production planning for semiconductor manufacturing via simulation optimization // In Proceedings of the 2011 Winter Simulation Conference, IEEE, Inc., Tucson, AZ, USA, pp. 3617–3627.

Li Y., Wu J., Ping Y., Kou W., Han Z. (2011). NetLogo-based simulation and analysis of college confidential project management // Computer Technology and Development.

Yan Liu, Soemon Takakuwa Modeling the materials handling in a container terminal using electronic real-time tracking data // Proceedings of the 2011 Winter Simulation Conference S. Jain, R.R. Creasey, J. Himmelspach, K.P. White, and M. Fu, eds. P.1596-1604.
In this paper, all of the operational activities of an actual container terminal in Japan are simulated to analyze the processing time and the bottlenecks of the operations flows. The method for collecting the required data for performing simulation is described, especially by making use of electronic real-time tracking data that is accumulated from the information systems. The procedure is applied to an actual container terminal in a port. It is found that the information obtained by performing simulation is effective for analyzing the performance of the operation.

Liu Z., Chua D.K.H., Wee K.H. A simulation model for spatial scheduling of dynamic block assembly in shipbuilding // Journal of Engineering, Project, and Production Management. 2011, 1(1), P.3-12.

Lychkina N.N., Andrianov D.L., Morozova Y.A. Social sphere modeling based on system dynamics methods, - 29th International System dynamics conference, Washington, D.C., 24-28 July 2011 (http://www.systemdynamics.com)

Natalia N. Lychkina, Yulia A. Morozova Stratification of Socio-economic Systems Based on the Principles of the Multi-modeling in a Heterogeneous Information-analytical Environment // The 2nd International Multi-Conference on Complexity, Informatics and Cybernetics: IMCIC 2011 March 27th - 30th, 2011 in Orlando, Florida, USA.

Lychkina N.N., Morozova Y.A., Shults D.N. Stratification of Socio-Economic Systems Based on the Principles of the Multi-Modeling in a Heterogeneous Information-Analytical Environment // 2nd International Multi-Conference on Complexity, Informatics and Cybernetics: IMCIC, Orlando, Florida, USA: International Institute of Informatics and Cybernetics, March 27-30, 2011 (http://www.2011iiisconferences.org/imcic)

Maharaj S., McCaldin T., Kleczkowski A. (2011). A Participatory Simulation Model for Studying Attitudes to Infection Risk // In Proceedings of the Summer Computer Simulation Conference 2011, ACM Digital Library, July 2011.
This paper describes work in progress in developing an agent based participatory simulation tool to be used in experiments to investigate human attitudes to the risk of being infected by disease.

Mahfouz, A., Shea, J., Arisha, A. Simulation based optimisation model for the lean assessment in SME: a case study // In Proceedings of the 2011 Winter Simulation Conference, IEEE, Inc., Tucson, AZ, USA, pp. 2408–2418.

Manzo G. (2011). Relative Deprivation in Silico: Agent-based Models and Causality in Analytical Sociology // in P. Demeulenaere (ed.), Analytical Sociology and Social Mechanisms, Cambridge, Cambridge University Press, ch. 13, pp.266-308.

Marquez B.Y., Espinoza-Hernandez I., Castanon-Puga M., Castro J.R., Suarez E.D. (2011). Distributed Agencies Applied to Complex Social Systems, a Multi-Dimensional approach // Proceedings of 2011 The 2nd International Conference on Next Generation Information Technology (ICNIT), 21-23 June 2011, pp. 213-219.
This work has as its main objective to apply the distributed agency methodology, which consists of several techniques used in computer science, to solve complex social problems. This approach allows the possibility of analyzing data from a macro level to a micro level where the intermediate part is highlighted, all in an organized integration of a social simulation displayed on geographic information with natural language quantifiers.

McDonnell S., Zellner M. (2011). Exploring the effectiveness of bus rapid transit a prototype agent-based model of commuting behavior // Transport Policy 18(6): 825-835.

Moussaida M., Helbing D., Theraulaza G. How simple rules determine pedestrian behavior and crowd disasters // PNAS. 2011. Vol. 108, no. 17. P. 6884–6892.

Nan N. (2011). Capturing bottom-up information technology use processes: A Complex adaptive systems model // Management Information Systems Quarterly, 35(2), pp.505-532.

Niazi Muaz; Hussain Amir (2011). Agent-based computing from multi-agent systems to agent-based models: A visual survey // Scientometrics. 89 (2): 479–499.

Niazi M.A., Hussain A. (2011). A Novel Agent-Based Simulation Framework for Sensing in Complex Adaptive Environments // Sensors Journal, IEEE, 11(2) doi: 10.1109/JSEN.2010.2068044.

Noor Talal H., Sheng Quan Z. (2011). Trust as a Service: A Framework for Trust Management in Cloud Environments // Proceedings of the 2011 12th International Conference on Web Information System Engineering (WISE), 12-14 October 2011, pp. 314-321.
In this paper, we propose the “Trust as a Service” framework to improve ways on trust management in cloud environments. In particular, we introduce an adaptive credibility model that distinguishes between credible trust feedbacks and malicious feedbacks by considering cloud service consumers’ capability and majority consensus of their feedbacks. The approaches have been validated by the prototype system and experimental results.

Victor Okolnishnikov. Development of Process Control Systems with the Use of Emulation Models // International Journal of Mathematics and Computers in Simulation. Issue 6, Volume 5, 2011, P. 553 – 560.

Victor Okolnishnikov. Emulation models for testing of process control systems // Proceedings of the 5th International Conference on Applied Mathematics, Simulation, Modelling (ASM'11), Corfu Island, Greece, July 14-16, 2011, P. 80 – 83.

Olson I.C., Horn M. (2011). Modeling on the Table: Agent-Based Modeling in Elementary School with NetTango // Proceedings of 10th International Conference on Interaction Design and Children (short paper), Ann Arbor, MI. June, 2011.

Olson I.C., Leong Z.A., Wilensky U., Horn M.S. (2011). «It’s just a toolbar!» Using tangibles to help children manage conflict around a multi-touch tabletop // In Proc. of the fifth international conference on Tangible, Embedded and Embodied Interaction (TEI’11), Funchal, Portugal. ACM New York. pp. 29-36.

Otcenaskova T., Bures V., Cech P. (2011). Multi-agent simulations in decision support: Specifics of the biological incident management // Mathematics and Computers in Biology, Business, and Acoustics.

Parfyonov Y.E. Choice of mathematical apparatus to develops imitating models of information systems // Системи обробки інформації, випуск 3 (93), ISSN 1681-7710, 2011, c.69-72.
Modeling is a powerful method of scientific knowledge, where a real object is represented by a model. The main types of modeling are mathematical and full-scale modeling. Full-scale modeling has rather limited application. In most cases, preference is given to the use of mathematical modeling. In order to develop adequate mathematical models of processes occurring in in-formation systems, it is important to choose appropriate mathematical apparatus. The article is devoted to analysis of the issues-concerning choice of mathematical formalism to develop models of information systems.

Patarakin E., Yarmakhov B., Burov V. (2011). Agent based simulation activities within the wiki system // Educational Technology & Society. pp. 407-422. (In Russian).

Pereda M., Zamarreno J.M. (2011). Agent-based modeling of an activated sludge process in a batch reactor // Proceedings of the 2011 19th Mediterranean Conference on Control & Automation (MED), 20-23 June 2011, pp. 1128-1133.
The aim of this work is to study the feasibility of using agent-based modeling to study the activated sludge process. A model in NetLogo has been proposed, and experiments have been developed comparing the model behavior with a classical.

Petreska I., Kefalas P., Gheorghe M. (2011). A framework towards the verification of emergent properties in spatial multi-agent systems // Proceedings of the Workshop on Applications of Software Agents, pp. 37-44.

Plinere D., Borisov A. A negotiation-based multi-agent system for supply chain management // Information Technology and Management Science, vol. 49, pp. 128-132, Dec. 2011.

Rand William; Rust Roland T. (2011). Agent-based modeling in marketing: Guidelines for rigor // International Journal of Research in Marketing. 28 (3): 181–193. doi:10.1016/j.ijresmar.2011.04.002.

Rebaudo F., Crespo-Perez V., Silvain J-F., Dangles O. (2011). Agent-Based Modeling of Human-Induced Spread of Invasive Species in Agricultural Landscapes: Insights from the Potato Moth in Ecuador // Journal of Artificial Societies and Social Simulation (JASSS), 14 (3) 7. (June 2011).

Stephen D. Roberts Tutorial on the simulation of healthcare systems // Proceedings of the 2011 Winter Simulation Conference S. Jain, R.R. Creasey, J. Himmelspach, K.P. White, and M. Fu, eds. P.1408-1410.
For a variety of reasons, simulation has enjoyed widespread application in health care and health care delivery systems. Although the dominant modeling methodology is discrete event simulation, numerous studies employ system dynamics, agent-based simulation, and hybrid/combined methods. Software has been increasingly adapted to health care through enhanced visualizations and modeling. Virtually every health care environment has been studied using simulation including hospitals, extended care, rehabilitation, specialty care, long-term care, public health, among others. Frequent problems are patient flow, staffing, works schedules, facilities capacity and design, admissions/scheduling, appointments, logistics, and planning. Health care problems are especially complicated by the fact that «people serve people», meaning people are both the customer and the supply. The customers arrive through a complex decision process that produces uncertain demand. The response is an even more complex organization of health care resources, each of which play a distinctive and overlapping role, providing a unique simulation challenge.

Rumyantsev Mikhail I. Simulation of financial institutions activity in transitional economies // In Proceedings of Regional Conference «Actual Issues of Modern Economic Science and International Relations» in Dnepropetrovsk, Ukraine, November 25-26, 2011. – Vol. 2, pp. 53-63. – ISBN 978-617-645-006-1.
The paper reviews the concepts of system dynamics and its applications to the simulation modeling of financial institutions daily activity. While widely applicable, the approach is of a particular interest in transitional and developing economies. The hybrid method of banking business processes re-engineering based on a combination of system dynamics, queuing theory and ordinary differential equations (Kolmogorov equations) is introduced. By the way of method illustration, we consider the promotion of a set of banking products among some categories of clients.

Rush D. (2011). A simulation of evolving sustainable technology through social pressure // Proceedings of the 2011 AAAI Fall Symposium, pp. 117-126.
In this paper we develop a model to simulate the evolution of a pollution-free resource gathering technology that is initially less efficient but ultimately reaches parity with polluting technology.

Sajedinejad, A., Mardani, S. SIMARAIL: Simulation based optimization software for scheduling railway network // In Proceedings of the 2011 Winter Simulation Conference, IEEE, Inc., Tucson, AZ, USA, pp. 3735–3746.

Salamon T. (2011). Design of Agent-Based Models: Developing Computer Simulations for a Better Understanding of Social Processes // Repin, Czech Republic: Bruckner Publishing. [Website]

Semyonov С. An integrated resource-based approach to port and terminal simulation modelling // Proceedings of The 15th International Conference on Harbour, Maritime & Multimodal Logistics Modeling and Simulation HMS, 2013. P. 13-17.

Sengupta P., Wilensky U. (2011). Lowering the Learning Threshold: Multi-Agent-Based Models and Learning Electricity // In Khine M.S., Saleh I.M (Eds.). Dynamic Modeling: Cognitive Tool for Scientific Inquiry. Springer, New York, NY.

Shelley T., Lyons L., Zellner M., Minor E. (2011). Evaluating the embodiment benefits of a paper-based TUI for educational simulations // Proceedings of CHI Extended Abstracts 2011, pp. 1375-1380.

Singh V.K., Modanwal N., Basak S. (2011). MAS coordination strategies and their application in disaster management domain // Proceedings of 2011 2nd International Conference on Intelligent Agent and Multi-Agent Systems (IAMA), 7-9 Sept. 2011, pp. 14-19.
In this paper, we have first presented a very brief survey characterizing the cooperation and coordination strategies that have been frequently used. Thereafter the paper progresses to explore the applicability of MAS formulations in disaster management domain. We have identified the characteristics and requirements of disaster management domain; described the ways in which MAS formulations can be used in this domain; and presented the preliminary results of our simulation experiment of a greedy approach to disaster recovery.

Sklar E. (2011). NetLogo, a multi-agent simulation environment // Artificial Life, 13(3): 303-311.

Sokolov B.V., Kokorin S.V., Ryzhikov Yu.I. Model and algorithm for combinational optimization of information system bandwidth // 25rd European Conference on Modelling and Simulation ECMS 2011 (June, 7–10, 2011, Krakow, Poland): Proceedings of conference.

Sokolovskaya Z.N. Imitation modeling of business processes in complex economic systems. // Праці Одеського політехнічного університету, Вип. 3(37), 2011, p.135-141.
The review of modern approaches and instruments of imitation modeling is adduced. The possibilities of using them in research of business processes of the complex economic objects are analyzed. The use of system-dynamic approach in modeling business processes of industrial enterprises is demonstrated.

Soriano G.C., Urano Y. (2011). Replication with state using the self-organizing map neural network // Proceedings of the 2011 13th International Conference on Advanced Communication Technology (ICACT), 13-16 Feb. 2011, pp. 383-388.
This paper proposes a modified form of random replication of data within a mobile peer-to-peer network based on predicting condition for a mobile node to replicate the object from it. It uses the unsupervised learning neural networks called the Self-Organizing Map by classifying the input attributes of each node and providing a training set - serving as a basis of identifying the nodes’ current state. To test the functionality of the technique, a simulation was developed in a multi-agent based modelling environment called the NetLogo and observations are compared with the proposed scheme with the existing algorithm.

Dirk Steinhauer The Simulation Toolkit Shipbuilding (STS) – 10 Years of Cooperative Development and Interbranch Applications // Материалы конференции COMPIT 2011 (European Conference on Computer and IT Applications in the Maritime Industries).
At Flensburger Shipyard simulation has been established as the main tool to support the decisions in production facility planning as well as in production planning and control. Because the available simulation tools are not sufficient for the usage in shipbuilding Flensburger Shipyard started the development of the Simulation Toolkit Shipbuilding (STS) in the year 2000. The STS contains a large variety of simulation tools for material flow modelling, model management, execution strategies and output analysis not strongly related to shipbuilding any more. It is further developed and used within the international cooperation SimCoMar and in the interbranch cooperation SIMoFIT.

Stonedahl F., Wilensky U. (2011). Finding Forms of Flocking: Evolutionary Search in ABM Parameter-Spaces // In Multi-Agent-Based Simulation XI, T. Bosse, A. Geller, & C. M. Jonker (Eds). Lecture Notes in Computer Science. Springer Berlin / Heidelberg. Vol. 6532. pp. 61-75.

Stonedahl F., Wilkerson-Jerde M., Wilensky U. (2011). MAgICS: Toward a Multi-Agent Introduction to Computer Science // In M.Beer, M.Fasli, and D. Richards (Eds.) Multi-Agent Systems for Education and Interactive Entertainment: Design, Use and Experience. IGI Global. pp.1-25.

Tarasov V.N., Konnov A.L. The analysis of productivity of the network of the campus on the basis of imitating modelling // Вестник ОГУ №4 (123), апрель 2011. P.147-151.
In work the technique of research of a LAN of 1st and 2nd levels which are in turn subnets of corporate network OSU is resulted. For research of such networks the program system of discretely_event modeling Opnet Modeler is used. The method of decomposition of networks is applied to increase of degree of adequacy of modeling on a subnet proceeding from the real traffic.

Uhlig, T., Rose, O. Simulation-based optimization for groups of cluster tools in semiconductor manufacturing using simulation annealing // In Proceedings of the 2011 Winter Simulation Conference, IEEE, Inc., Tucson, AZ, USA, pp. 1857–1868.

Ulbinaitė A., Kučinskienė М., Le Moullec Y. Conceptualising and Simulating Insurance Consumer Behaviour: an Agent-Based-Model Approach // International Journal of Modeling and Optimization. Vol. 1. No. 3. August 2011.

Vasileva, S. Algorithm for Primary Copy Locking with Timestamp Ordering. // Proceedings of the V International Conference on Information Systems and GRID Technologies, 27-28 may 2011, Sofia, Bulgaria, organized by University of Sofia «St. Kliment Ohridski» and BulAIS - Bulgarian Chapter of AIS, St. Kliment Ohridski University Press, Sofia, Bulgaria, pp. 236-247. Available at: link.

Vasileva, S., A. Milev. Two-phase lock modeling algorithms using timestamp ordering in distributed databases. // Proceedings of the International Conference Automatics and Informatics’11, 2 – 6 October 2011, Sofia, Bulgaria, pp. В-359 – В-362.

Vattam S.S., Goel A.K., Rugaber S. (2011). Behavior Patterns: Bridging conceptual models and agent-based simulations in interactive learning environments // Proceedings of the 2011 IEEE 11th International Conference on Advanced Learning Technologies, pp.139-141.

Vinatier F., Lescurret F., Duyck P.-F., Martin O., Senoussi R., Tixier P. (2011). Should I Stay or Should I Go? A Habitat-Dependent Dispersal Kernel Improves Prediction of Movement. PLoS ONE, 6, e21115.

Wildman W., Sosis R. (2011). Stability of Groups with Costly Benefits and Practices // Journal of Artificial Societies and Social Simulation (JASSS), 14 (3) 6. (June 2011).

Witkowski T., Antczak P., Antczak A. Simulation modeling of manufacturing systems for the serial route and the parallel one // World Academy of Science, Engineering and Technology International Journal of Industrial and Manufacturing Engineering, Vol:5, No:1, 2011. С.217-222.
In the paper we discuss the influence of the route flexibility degree, the open rate of operations and the production type coefficient on makespan.

Xia H., Jia Z., Ju L., Li X., Zhu Y. (2011). A subjective trust management model with multiple decision factors for MANET based on AHP and fuzzy logic rules // Proceedings of 2011 IEEE/ACM International Conference on Green Computing and Communications (GreenCom), 4-5 Aug. 2011, pp. 124-130.

Levent Yilmaz, Guangyu Zou, and Osman Balci A Robust Evolutionary Strategy for Generative Validation of Agent-Based Models Using Adaptive Simulation Ensembles // In Proceedings of the 2011 Winter Simulation Conference (Phoenix, AZ, Dec. 11-14). IEEE, Piscataway, NJ, 2011. pp. 2852-2864.

Zhao M., He Q. (2011). A simulation system of social economic // Computer and Information Science, vol.4, No.5, pp.97-103.
In this essay, a simulation model, which emulates the change of middle class number in an economy environment after the government gives subsidies to the poverty, is made to infer the governmental macro-control’s influence to the national economy. The result indicates that the government plays a significant role in achieving a balance of the rich and the poverty by levying tax.