Solving Robust EOQ Model Using Genetic Algorithm

We consider a (worst-case) robust optimization version of the Economic Order Quantity (EOQ) model. Order setup costs and inventory carrying costs are assumed to have uncertainty in their val-ues, and the uncertainty description of the two parameters is supposed to be given by an ellipsoidal represen...

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Bibliographic Details
Published inManagement science & financial engineering Vol. 13; no. 1; pp. 35 - 53
Main Author Lim, Sungmook
Format Journal Article
LanguageEnglish
Published Seoul 한국경영과학회 01.05.2007
KORMS
Subjects
경영학
Uncertainty
EOQ Model
Monte Carlo Simulation
Robust Optimization
Genetic Algorithm
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ISSN2287-2043
2287-2361

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Summary:We consider a (worst-case) robust optimization version of the Economic Order Quantity (EOQ) model. Order setup costs and inventory carrying costs are assumed to have uncertainty in their val-ues, and the uncertainty description of the two parameters is supposed to be given by an ellipsoidal representation. A genetic algorithm combined with Monte Carlo simulation is proposed to approxi-mate the ellipsoidal representation. The objective function of the model under ellipsoidal uncertainty description is derived, and the resulting problem is solved by another genetic algorithm. Computa-tional test results are presented to show the performance of the proposed method. KCI Citation Count: 1
Bibliography:SourceType-Scholarly Journals-1
ObjectType-General Information-1
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G704-000073.2007.13.1.004
ISSN:2287-2043
2287-2361