A genetic algorithm for supply chain configuration with new product development

摘要: Designing a multi-echelon multi-product multi-period supply chain model.Considering new product development effects in configuration.Developing priority based genetic algorithm to find the suitable solution at reasonable time. New has become increasingly important recently due highly competitive market place and economic reasons. Development production of products planning horizon require an efficient responsiveness network. As appear market, old could obsolete, then phased out. A generously persuasive parameter for developed problems is time which are introduced out also order maximum total profit.With consideration factors noted above, this study proposes design multi echelon period model incorporates their on configuration.In terms technique, overcome NP-hardness proposed model, applied introducing horizon, schedule network profit computational The accuracy validated small, medium large instances that have been solved using software LINGO, evaluate performance algorithm. Then, implementation fuzzy crossover mutation controllers described. It able regulate rates operators during search process. Finally, comparison done conventional GA controlled GA.