Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-540-48584-1_22
Title: Evolutionary algorithm for an inventory location problem
Authors: Chew, E.P. 
Lee, L.H. 
Rajaratnam, K.
Issue Date: 2007
Source: Chew, E.P.,Lee, L.H.,Rajaratnam, K. (2007). Evolutionary algorithm for an inventory location problem. Studies in Computational Intelligence 49 : 613-628. ScholarBank@NUS Repository. https://doi.org/10.1007/978-3-540-48584-1_22
Abstract: This paper deals with minimizing the cost in a joint location-inventory model with a single supplier supplying to multiple capitated distribution centers. The distribution center faces stochatic demands from multiple retailers. The problem is to determine how to assign retailers to distribution center within the service level constraints. The costs considered include the transportation cost, inventory holding cost and ordering cost. We develop an adaptive realcoded genetic algorithm to solve the problem. We conduct few experiment runs to compare the performance of the proposed method with some existing methods which include the simple genetic algorithm, the column generation method and the greedy method. For the non-capacitated case, the method shows very promising results with respect to both time and quality of the solutions. Similarly for the capacitated case, where the column generation method cannot be applied, the model is also significantly better than all the other methods, especially when the problem size is big. © Springer-Verlag Berlin Heidelberg 2007.
Source Title: Studies in Computational Intelligence
URI: http://scholarbank.nus.edu.sg/handle/10635/63124
ISBN: 3540485821
ISSN: 1860949X
DOI: 10.1007/978-3-540-48584-1_22
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