| Simulation-based optimization: practical introduction to simulation optimization |
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Winter Simulation Conference
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Proceedings of the 35th conference on Winter simulation: driving innovation
table of contents
New Orleans, Louisiana
SESSION: Introductory tutorials
table of contents
Pages: 71 - 78
Year of Publication: 2003
ISBN:0-7803-8132-7
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Winter Simulation Conference
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Downloads (6 Weeks): 13, Downloads (12 Months): 115, Citation Count: 10
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ABSTRACT
The merging of optimization and simulation technologies has seen a rapid growth in recent years. A Google search on "Simulation Optimization" returns more than six thousand pages where this phrase appears. The content of these pages ranges from articles, conference presentations and books to software, sponsored work and consultancy. This is an area that has sparked as much interest in the academic world as in practical settings. In this paper, we first summarize some of the most relevant approaches that have been developed for the purpose of optimizing simulated systems. We then concentrate on the metaheuristic black-box approach that leads the field of practical applications and provide some relevant details of how this approach has been implemented and used in commercial software. Finally, we present an example of simulation optimization in the context of a simulation model developed to predict performance and measure risk in a real world project selection problem.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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Gerencsér, L. 1999. "Optimization Over Discrete Sets Via SPSA," Proceedings of the IEEE Conference on Decision and Control, pp. 1791--1795.
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Laguna, M. and R. Martí 2002. "Neural Network Prediction in a System for Optimizing Simulations," IIE Transactions, (34) 3, pp. 273--282.
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Martí, R., M. Laguna and V. Campos 2002. "Scatter Search Vs. Genetic Algorithms: An Experimental Evaluation with Permutation Problems", to appear in Adaptive Memory and Evolution: Tabu Search and Scatter Search, Cesar Rego and Bahram Alidaee (eds.), Kluwer Academic Publishers, Boston.
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van Beers, W. C. M. and J. P. C. Kleijnen 2003. "Kriging for Interpolation in Random Simulation," Journal of the Operational Research Society, (54) 3, pp. 255--262.
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CITED BY 10
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Jay April , Marco Better , Fred Glover , James Kelly , Manuel Laguna, Enhancing business process management with simulation optimization, Proceedings of the 37th conference on Winter simulation, December 03-06, 2006, Monterey, California
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Michael C. Fu , Fred W. Glover , Jay April, Simulation optimization: a review, new developments, and applications, Proceedings of the 37th conference on Winter simulation, December 04-07, 2005, Orlando, Florida
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