Constrained optimization in simulation: a novel approach
AbstractThis paper presents a novel heuristic for constrained optimization of random computer simulation models, in which one of the simulation outputs is selected as the objective to be minimized while the other outputs need to satisfy prespeci¯ed target values. Besides the simulation outputs, the simulation inputs must meet prespeci¯ed constraints including the constraint that the inputs be integer. The proposed heuristic combines (i) experimental design to specify the simulation input combinations, (ii) Kriging (also called spatial correlation modeling) to analyze the global simulation input/output data that result from this experimental design, and (iii) integer nonlinear programming to estimate the optimal solution from the Kriging metamodels. The heuristic is applied to an (s, S) inventory system and a realistic call-center simulation model, and compared with the popular commercial heuristic OptQuest embedded in the ARENA versions 11 and 12. These two applications show that the novel heuristic outperforms OptQuest in terms of search speed (it moves faster towards high-quality solutions) and consistency of the solution quality.
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Bibliographic InfoPaper provided by Katholieke Universiteit Leuven in its series Open Access publications from Katholieke Universiteit Leuven with number urn:hdl:123456789/200609.
Length: 1-27 pages
Date of creation: Oct 2008
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Other versions of this item:
- Kleijnen, J.P.C. & Beers, W.C.M. van & Nieuwenhuyse, I. van, 2008. "Constrained Optimization in Simulation: A Novel Approach," Discussion Paper 2008-95, Tilburg University, Center for Economic Research.
- C0 - Mathematical and Quantitative Methods - - General
- C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
- C9 - Mathematical and Quantitative Methods - - Design of Experiments
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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"Customized Sequential Designs for Random Simulation Experiments: Kriging Metamodelling and Bootstrapping,"
2005-55, Tilburg University, Center for Economic Research.
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- Kleijnen, J.P.C., 2007.
"Kriging Metamodeling in Simulation: A Review,"
2007-13, Tilburg University, Center for Economic Research.
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- Driessen, L. & Brekelmans, R.C.M. & Hamers, H.J.M. & Hertog, D. den, 2001. "On D-Optimality Based Trust Regions for Black-Box Optimization Problems," Discussion Paper 2001-69, Tilburg University, Center for Economic Research.
- Sridhar Bashyam & Michael C. Fu, 1998. "Optimization of (s, S) Inventory Systems with Random Lead Times and a Service Level Constraint," Management Science, INFORMS, vol. 44(12-Part-2), pages S243-S256, December.
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