Title: Constrained optimization in simulation: a novel approach
Authors: Van Nieuwenhuyse, Inneke
Kleijnen, J.P.C.
van Beers, W.
Issue Date: Oct-2008
Publisher: K.U.Leuven - Faculty of Business and Economics
Series Title: FBE Research Report KBI_0822
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 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.
Publication status: published
KU Leuven publication type: IR
Appears in Collections:Research Center for Operations Management, Leuven

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