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  • 标题:Optimization of Material Supply Chain System Using Genetic Algorithm – A Proposed System
  • 本地全文:下载
  • 作者:Kalyani Devidas Desai ; Sanketa Ulhas Khupase ; Apurva Satish Kolapkar
  • 期刊名称:International Journal of Electronics, Communication and Soft Computing Science and Engineering
  • 印刷版ISSN:2277-9477
  • 出版年度:2012
  • 卷号:2
  • 期号:Special
  • 出版社:IJECSCSE
  • 摘要:The system is about managing the effective utiliz ation of raw materials needed in a particular manufacturing company so that it w ill produce minimum wastage and will maximize the profit. Every manufacturing company is connected to various suppliers and all the supplier companies are small scale companies so that they are not capable of appointing an expert person for managing the schedules of manufacturing company. These companies are required to manage their manufacturing process according to the schedules given to them. In any case if the schedule has b een changed they will have to manage their production accordingly, this needs additional production and time, so this can waste their time, material as well as finance, this is not affordable for all these small scale as well as manufacturing companies to whom they are providing material. To avoid all these problems, optimization of material supply chain system using genetic algorithm deals with changing schedules of the companies, reuse or proper utilization of materials effectively. The system is general ized that is it can be used w herever; there is a need of managing cost as well as changing schedules of any kind of manufacturing company. This is an intelligent system which will ma nage to take decision according to dynamic schedules of manufacturing comp any by itself using algorithms of A I (A rtificial intelligence).
  • 关键词:Optimization; Supply chain; Manufacture;Genetic algorithm; Crossover; Mutation; AI
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