TITLE:
Implementation of Hybrid Genetic Algorithm for CLSC Network Design Problem—A Case Study on Fashion Leather Goods Industry
AUTHORS:
Muthusamy Aravendan, Ramasamy Panneerselvam
KEYWORDS:
Industry Case, CLSC, Fashion Products, Leather Goods, Luggage Goods, Hybrid Genetic Algorithm (HGA), Meta-Heuristics, MINLP, Network Design, Reverse Supply Chain
JOURNAL NAME:
American Journal of Operations Research,
Vol.6 No.4,
July
13,
2016
ABSTRACT: The implementation of closed loop supply chain system is becoming essential for fashion leather products industry to ensure an economically sustainable business model and eco-friendly industrial practice as demanded by the environmental regulations, consumer awareness and the prevailing social consciousness. In this context, this research work addresses a closed loop supply chain network problem of fashion leather goods industry, with an objective of minimizing the total cost of the entire supply chain and also reducing the total waste from the end of life product returns. The research work commenced with a literature review on the reverse and closed loop supply chain network design problems of fashion and leather goods industry dealt in the past. Then, the identified CLSCND problem is solved using a mathematical model based on Mixed Integer Non-Linear Programme (MINLP) and then a suitable Hybrid Genetic Algorithm (HGA) developed for the CLSCND is implemented for obtaining optimum solution. Both the MINLP model and HGA are customized as per the CLSCND problem chosen and implemented for the industrial case of an Indian Fashion Leather Goods Industry. Finally, the solutions obtained for MINLP model in LINGO 15 and for HGA in VB.NET platform are compared and presented. The optimum solution obtained from the suitable HGA is illustrated as an optimum shipment pattern for the closed loop supply chain network design problem of the fashion leather goods industry case.