Iterative Simulation and Optimization Approach for Job Shop Scheduling Ketki Kulkarni, Jayendran Venkateswaran, Indian Institute of Technology Bombay. Winter Simulation Conference, 2014.

In this paper, we present an iterative scheme integrating simulation with an optimization model, for solving
complex problems, viz., job shop scheduling. The classical job shop scheduling problem which is NP-Hard,
has often been modelled as Mixed-Integer Programming (MIP) model and solved using exact algorithms (for
example, branch-and-bound and branch-and-cut) or using meta-heuristics (for example, Genetic Algorithm,
Particle Swarm Optimization and Simulated Annealing).
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Discrete Event Simulation Model of Asphalt Paving Operations Ramzi Labban, Simaan AbouRizk et al., Proceedings of the 2013 Winter Simulation Conference

Although research into simulation of construction continues to advance and thrive in the academic world, application of simulation in the construction industry remains limited. Stakeholders on construction projects have yet to adopt simulation as their default tool of choice for managing large complex projects, instead of traditional techniques, which are often inadequate. This paper describes the building of an asphalt paving simulator, as an example of the rigor and effort required in developing construction simulation models, and then briefly describes an alternative model building method currently being researched which may potentially make it easier and faster for stakeholders to quickly build construction simulation models.
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Prospective Healthcare Decision-Making By Combined System Dynamics, Discrete-Event And Agent-Based Simulation Anatoli Djanatliev, Reinhard German, Proceedings of the 2013 Winter Simulation Conference

Prospective Health Technology Assessment allows early decision making for innovative health care technologies. In our recent publications a hybrid simulation approach with System Dynamics and Agent-Based Modeling has been presented. This paper presents a mechanism to generate agents dynamically from SD models and extends the previously presented hybrid approach by process-oriented Discrete Event Simulation for hospital modeling.
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Business Process Modeling and Efficiency Improvement through an Agent-Based Approach Dario RUSSO, Franco PASSACANTANDO, Luigi GEPPERT, Luigi MANCA

This paper describes the results of a practical experience of business process improvement and change. the business modeling approach, carried out through an agent-based model, has been applied to an operational process with the aim to reduce the overlapping of the operational phases and to improve the time-efficiency. Simulation outcomes and results are discussed.
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The universal simulation tool is based on designs by Russian scientists Timofey Popkov.

Timofey Popkov, Business Development Director of XJ Technologiesdiscusses the specifics of simulation tools development and promotion in Russia and in international markets, as well as prospective trends in applying simulation techniques.
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Using simulation tools for strategic decision making Mark Paich. PricewaterhouseCoopers Technology Forecast 2010, Issue 1.

Dr. Mark Paich provides examples of Decisio’s success in using AnyLogic and other simulation tools to help executives at large enterprises make major transformation decisions.
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Investigating Output Accuracy for a Discrete Event Simulation Model and an Agent Based Simulation Model Mazlina Abdul Majid, Uwe Aickelin, Peer-Olaf Siebers. 2009 INFORMS at University of Warwick, June 25-27, Coventry, U.K.

In this paper, we investigate output accuracy for a Discrete Event Simulation (DES) model and Agent Based Simulation (ABS) model. The purpose of this investigation is to find out which of these simulation techniques is the best one for modelling human reactive behaviour in the retail sector. In order to study the output accuracy in both models, we have carried out a validation experiment in which we compared the results from our simulation models to the performance of a real system. Our experiment was carried out using a large UK department store as a case study.
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Dynamic Learning in Human Decision Behavior for Evacuation Scenarios under BDI Framework Seungho Lee, Young-Jun Son. 2009 INFORMS at University of Warwick, June 25-27, Coventry, U.K.

A novel approach to represent learning in human decision behavior for evacuation scenarios is proposed under the context of an extended Belief-Desire-Intention framework. In particular, we focus on how a human adjusts his perception process (involving a Bayesian belief network) in Belief Module dynamically against his performance in predicting the environment as part of his decision planning function. To this end, a Q-learning algorithm (reinforcement learning algorithm) is employed and further developed.
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Real Options and System Dynamics Aproach To Model Value of Implementing a Project Specific Dispute Resolution Process in Construction Projects Carol C. Menassa, Feniosky Peña Mora. 2009 Winter Simulation Conference (WSC’09), December 13-16, Austin, TX, USA

This paper presents a methodology to study the effect of different resolution strategies on the value of the investment in a project-specific dispute resolution ladder (DRL) using option/real option theories from financial engineering, process centric modeling, and system dynamics methodology.
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Agent-based Modeling and Simulation Charles M. Macal, Michael J. North. 2009 Winter Simulation Conference (WSC’09), December 13-16, Austin, TX, USA

Agent-based modeling and simulation (ABMS) is a new approach to modeling systems comprised of autonomous, interacting agents. Computational advances have made possible a growing number of agent-based models across a variety of application domains. Applications range from modeling agent behavior in the stock market, supply chains, and consumer markets, to predicting the spread of epidemics, mitigating the threat of bio-warfare, and understanding the factors that may be responsible for the fall of ancient civilizations.
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