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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Modelling and Analysing Cargo Screening Processes: a Project Outline Peer-Olaf Siebers, Uwe Aickelin, David Menachof, Galina Sherman, Peter Zimmerman. 2009 INFORMS at University of Warwick, June 25-27, Coventry, U.K.

The efficiency of current cargo screening processes at sea and air ports is unknown as no benchmarks exists against which they could be measured. Some manufacturer benchmarks exist for individual sensors but we have not found any benchmarks that take a holistic view of the screening procedures assessing a combination of sensors and also taking operator variability into account. Just adding up resources and manpower used is not an effective way for assessing systems where human decision-making and operator compliance to rules play a vital role.
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The Impact of Human Decision Makers’ Individualities on The Wholesale Price Contract’s Efficiency: Simulating The Newsvendor Problem Stavrianna Dimitriou, Stewart Robinson, Kathy Kotiadis. 2009 Winter Simulation Conference (WSC’09), December 13-16, Austin, TX, USA

Suppliers and retailers in the newsvendor setting need to submit their pricing and inventory decisions respectively, well before actual customer demand is realized. In the literature they have both been typically considered as perfectly rational optimizers, exclusively interested in their own respective benefits. Under the above set of conditions the wholesale price-only contract has long been analytically proven as inefficient.
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Toward Simulation-Based Real-Time Decision-Support Systems for Emergency Departments Yariv N. Marmor, Segev Wasserkrug, Avraham Shtub. 2009 Winter Simulation Conference (WSC’09), December 13-16, Austin, TX, USA

Emergency Departments (EDs) require advanced support systems for monitoring and controlling their processes: clinical, operational, and financial. A prerequisite for such a system is comprehensive operational information (e.g. queueing times, busy resources,…), reliably portraying and predicting ED status as it evolves in time. To this end, simulation comes to the rescue, through a two-step procedure that is hereby proposed for supporting real-time ED control.
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First Steps Towards a General SysML Model for Discrete Processes in Production Systems Oliver Schönherr, Oliver Rose. 2009 Winter Simulation Conference (WSC’09), December 13-16, Austin, TX, USA

In many areas of science, like computer science or electrical engineering, modeling languages have been established, however, this is not the case in the field of discrete processes (Weilkiens 2006). There are two reasons which motivate such a development.
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Are Simulation Standards in Our Future? Hans Ehm, Leon McGinnis, Oliver Rose. 2009 Winter Simulation Conference (WSC’09), December 13-16, Austin, TX, USA

This panel seeks to initiate a discussion within the production system simulation community about a fundamental change in the way we think about, teach, and implement production system simulation. Today, production system simulation, while based on formal simulation languages, is largely an artistic process.
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Simulating The Effect on The Energy Efficiency of Smart Grid Technologies Albert Molderink, Maurice G.C. Bosman, Vincent Bakker, Johann L. Hurink, Gerard J.M. Smit. 2009 Winter Simulation Conference (WSC’09), December 13-16, Austin, TX, USA

The awareness of the greenhousegas effect and rising energy prices lead to initiatives to improve energy efficiency. These initiatives range from micro-generation, energy storage and efficient appliances to controllers with optimization objectives. Although these technologies are promising, their introduction may rise further questions. The implementation of such initiatives may have a severe impact on the electricity infrastructure. If several of these initiatives are introduced in a combined way, it is difficult to analyse their overall impact.
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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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Hybrid Simulation and Optimization-Based Capacity Planner for Integrated Photovoltaic Generation with Storage Units Esfandyar M. Mazhari. 2009 Winter Simulation Conference (WSC’09), December 13-16, Austin, TX, USA

Unlike fossil-fueled generation, solar energy resources are geographically distributed and highly intermittent, which makes their direct control difficult and requires storage units. The goal of this research is to develop a flexible capacity planning tool, which will allow us to obtain a most economical mixture of capacities from solar generation as well as storage while meeting reliability requirements against fluctuating demand and weather conditions. The tool is based on hybrid (system dynamics and agent-based models) simulation and meta-heuristic optimization.
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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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