Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/15288
Title: Optimizing replenishment polices using genetic algorithm for single-warehouse multi-retailer system
Authors: Yang, W
Chan, FTS 
Kumar, V
Keywords: Genetic Algorithms
Multi-retailer
Replenishment policy
Supply chain management
Warehouse
Issue Date: 2012
Publisher: Pergamon Press
Source: Expert systems with applications, 2012, v. 39, no. 3, p. 3081-3086 How to cite?
Journal: Expert systems with applications 
Abstract: Coordinating inventory and transportation policies can lead to substantial cost savings and improved service levels especially when the companies relay on third-party logistics providers to transport the products across the supply chain. In this paper, therefore focus has been given on a supply chain system of multi-supplier, single warehouse and multi-retailer with backlogging and transportation capacity. The paper aims to suggest replenishment policies that can minimize system-wide cost by taking advantage of quantity discounts in the transportation cost structures. The problem considered in this paper has been formulated as an integer programming model. The supply chain problem is usually complex and involves massive calculations hence it is difficult to obtain an optimal solution. Therefore, to overcome this issue a Genetic Algorithm (GA) based approach has been suggested to resolve the problem. The computational results demonstrate the robustness and efficacy of the GA in optimizing replenishment policies.
URI: http://hdl.handle.net/10397/15288
ISSN: 0957-4174
EISSN: 1873-6793
DOI: 10.1016/j.eswa.2011.08.171
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