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An ESPC algorithm based approach to solve inventory deployment problem

Chan, F.T.S. and Kumar, Vikas and Wong, T.C. (2007) An ESPC algorithm based approach to solve inventory deployment problem. In: OSCM07 - 2nd International Conference on Operations and Supply Chain Management, 18–20 May 2007, Bangkok, Thailand.

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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.

Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Subjects:Engineering > Production engineering
Computer Science > Algorithms
DCU Faculties and Centres:DCU Faculties and Schools > DCU Business School
Published in:Proceedings of The 2nd International Conference on Operations and Supply Chain Management. (91-101).
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:15779
Deposited On:02 Nov 2010 12:09 by Dr Vikas Kumar. Last Modified 02 Nov 2010 12:09

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