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Constrained Optimization in Simulation: A Novel Approach

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Author Info
Kleijnen, J.P.C.
Beers, W.C.M. van
Nieuwenhuyse, I. van (Tilburg University, Center for Economic Research)

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Abstract

This 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 mod- eling) 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 Krig- ing 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 outper- forms OptQuest in terms of search speed (it moves faster towards high-quality solutions) and consistency of the solution quality.

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Paper provided by Tilburg University, Center for Economic Research in its series Discussion Paper with number 2008-95.

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Date of creation: 2008
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Handle: RePEc:dgr:kubcen:200895

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Find related papers by JEL classification:
C0 - Mathematical and Quantitative Methods - - General
C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General
C9 - Mathematical and Quantitative Methods - - Design of Experiments

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  1. Kleijnen, Jack P.C. & Deflandre, David, 2006. "Validation of regression metamodels in simulation: Bootstrap approach," European Journal of Operational Research, Elsevier, vol. 170(1), pages 120-131, April. [Downloadable!] (restricted)
  2. van Beers, Wim C.M. & Kleijnen, Jack P.C., 2008. "Customized sequential designs for random simulation experiments: Kriging metamodeling and bootstrapping," European Journal of Operational Research, Elsevier, vol. 186(3), pages 1099-1113, May. [Downloadable!] (restricted)
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  3. Driessen, Lonneke & Brekelmans, Ruud & Gerichhausen, Marloes & ...,, 2006. "Why methods for optimization problems with time-consuming function evaluations and integer variables should use global approximation models," Discussion Paper 4, Tilburg University, Center for Economic Research. [Downloadable!]
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