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Generalized response surface methodology : a new metaheuristic

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Author Info
Kleijnen, Jack P.C. (Tilburg University, Center for Economic Research)

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Abstract

Generalized Response Surface Methodology (GRSM) is a novel general-purpose metaheuristic based on Box and Wilson.s Response Surface Methodology (RSM). Both GRSM and RSM estimate local gradients to search for the optimal solution. These gradients use local first-order polynomials. GRSM, however, uses these gradients to estimate a better search direction than the steepest ascent direction used by RSM. Moreover, GRSM allows multiple responses, selecting one response as goal and the other responses as constrained variables. Finally, these estimated gradients may be used to test whether the estimated solution is indeed optimal. The focus of this paper is optimization of simulated systems.

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Paper provided by Tilburg University, Center for Economic Research in its series Discussion Paper with number 77.

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Date of creation: 2006
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Handle: RePEc:dgr:kubcen:200677

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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, J.P.C. & Hertog, D. den & Ang, n, 2002. "Response surface methodology's steepest ascent and step size revisited," Discussion Paper 64, Tilburg University, Center for Economic Research. [Downloadable!]
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  2. Kleijnen, J.P.C., 1997. "Experimental design for sensitivity analysis, optimization, and validation of simulation models," Discussion Paper 52, Tilburg University, Center for Economic Research. [Downloadable!]
  3. Kleijnen, Jack P.C. & den Hertog, Dick & Angun, Ebru, 2006. "Response surface methodology's steepest ascent and step size revisited: Correction," European Journal of Operational Research, Elsevier, vol. 170(2), pages 664-666, April. [Downloadable!] (restricted)
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This page was last updated on 2009-11-25.

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