Submit your paper : editorIJETjournal@gmail.com Paper Title : Electronic components supply chain management using evolutionary algorithm ISSN : 2395-1303 Year of Publication : 2020 10.29126/23951303/IJET-V6I5P6 MLA Style: -Mr.G.Sreeraj ., Mr.M.S.Sabari, M.E ., Dr.R.Umamaheshwari M.E., Ph.D., " Electronic components supply chain management using evolutionary algorithm" Volume 6 - Issue 5(36-40) September - October,2020 International Journal of Engineering and Techniques (IJET) ,ISSN:2395-1303 , www.ijetjournal.org APA Style: -Mr.G.Sreeraj ., Mr.M.S.Sabari, M.E ., Dr.R.Umamaheshwari M.E., Ph.D., " Electronic components supply chain management using evolutionary algorithm" Volume 6 - Issue 5(36-40) September - October,2020 International Journal of Engineering and Techniques (IJET) ,ISSN:2395-1303 , www.ijetjournal.org Abstract - Electronic components Supply Chain management for environmental concerns a technique based on neural networks to optimize inventory in the whole electronic components supply chain. We focus on to specifically determine the dynamic nature of the excess stock level and shortage level required for inventory optimization in the Electronic components supply chain such that the total Electronic components Supply Chain management for environmental concerns cost is minimized. The complexity of the problem increases when more products and multiple agents are involved in Electronic components Supply Chain management for environmental concerns process that has been resolved in this work. One important aspect of supply chain management is the maintenance of an efficient and cost effective system for the distribution of goods or products to retailing outlets. We show in this paper how an evolutionary algorithm (EA) can play an effective role in this aspect. Besides being an effective and efficient optimization tool capable of handling problems of significant computational complexity, it enjoys great flexibility in coping with the constraints of typical real-life supply chain problems. Our work considers the problem of managing a distribution network for replenishing the supply of fuel to refueling stations located all over the island. It is designed to generate a set of routes for a fleet of fuel trucks. The trucks are dispatched according to a pre-specified plan to replenish the supply of the various refueling stations subject to several dynamic constraints. Our solution methodology is an EA capable of generating approximate solutions with reasonable computational time. Reference [1] Sarmiento, A. Rabelo, L. Lakkoju, R. Moraga, R., “Stability analysis of the supply chain by using neural networks and genetic algorithms”, Proceedings of the winter Simulation Conference, pp: 1968-1976, 2007. [2] Joines, J.A. Gupta, D. 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