Please use this identifier to cite or link to this item: https://scholar.utcc.ac.th/handle/6626976254/950
Title: An ESPC Algorithm Based Approach to Solve Inventory Deployment Problem
Authors: Chan, Felix T. S. 
Kumar, V. 
Wong, T. C. 
Issue Date: 2007
Publisher: University of the Thai Chamber of Commerce
Source: Felix T. S. Chan, V. Kumar, T. C. Wong (2007) An ESPC Algorithm Based Approach to Solve Inventory Deployment Problem.
Conference: Proceedings of the 2nd International Conference on Operations and Supply Chain Management 
Abstract: Global competitiveness has enforced the hefty industries to become more customized. To compete in the market they are targeting the customers who want exotic products, and faster and reliable deliveries. Industries are exploring the option of satisfying a portion of their demand by converting strategically placed products, this helps in increasing the variability of product produced by them in short lead time. In this paper, authors have proposed a new hybrid evolutionary algorithm named Endosymbiotic-Psychoclonal (ESPC) algorithm to determine the amount and type of product to stock as a semi product in inventory. In the proposed work the ability of previously proposed Psychoclonal algorithm to exploit the search space has been increased by making antibodies and antigen more cooperative interacting species. The efficacy of the proposed algorithm has been tested on randomly generated datasets and the results obtained, are compared with other evolutionary algorithms such as Genetic Algorithm (GA) and Simulated Annealing (SA). The comparison of ESPC with GA and SA proves the superiority of the proposed algorithm both in terms of quality of the solution obtained, and convergence time required to reach the optimal /near optimal value of the solution.
URI: https://scholar.utcc.ac.th/handle/6626976254/950
Rights: This work is protected by copyright. Reproduction or distribution of the work in any format is prohibited without written permission of the copyright owner.
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