A new manufacturing resource allocation method for supply chain optimization using extended genetic algorithm

摘要: In distributed manufacturing environments, the real competitive edge of an enterprise is directly related to optimization level its supply chain deployment in general, and, particular, how it allocates diverse resources optimally. This faced with increasing challenges caused by conflicting objectives integration over resources. paper presents a new resource allocation method using extended genetic algorithm (GA) support multi-objective decision-making for deployment. A mathematical model proposed evaluate, select, and sequence candidate allocated sub-tasks composing chain, dealing trade-offs among multiple including similarity, time, cost, quality, service. An GA approach problem-specific two-dimensional representation scheme, selection operator, crossover mutation operator solve optimally designing chromosome containing two kinds information, i.e., sequencing. case study carried out demonstrate effectiveness efficiency approach.