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  • 标题:SUPPLY CHAIN OPTIMIZATION USING GENETIC ALGORITHM IN INDUSTRY MANUFACTURE: A SYSTEMATIC LITERATURE REVIEW
  • 本地全文:下载
  • 作者:MASMUR TARIGAN ; FORD LUMBAN GAOL
  • 期刊名称:Journal of Theoretical and Applied Information Technology
  • 印刷版ISSN:1992-8645
  • 电子版ISSN:1817-3195
  • 出版年度:2021
  • 卷号:99
  • 期号:16
  • 语种:English
  • 出版社:Journal of Theoretical and Applied
  • 摘要:One of the supply chain and exchange of material information from suppliers to final consumers is the supply chain idea. Customer needs fluctuate or go unnoticed as a result of the increase, decrease, and cancellation of consumer interest, and supply chains play a role in market competition. The thorough literature review aims to find a more accurate and efficient application of genetic algorithms in the manufacturing industry for supply chain optimization. from the journal search results, 171 journals were found for the period 2016-2021, after review, 118 journals that were relevant to the research were selected, from these relevant journals there were 23 selected journals. Of these 23 journals, there are still gaps in the criteria for research questions, based on search strings, process criteria, so that further research on supply chain optimization using genetic algorithms can still be done.
  • 关键词:Genetics;Algorithms;Supply Chain;Optimization;Effective;Efficiency;Accura
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