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Supply chain optimization using genetic algorithm in industry manufacture: A systematic literature review

  • Masmur Tarigan
  • , Ford Lumban Gaol
  • , Harco Lesie Hendric Spits Warnars
  • , Benefano Soewito
  • , Tokuro Matsuo

Research output: Contribution to journalReview articlepeer-review

Abstract

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.

Original languageEnglish
Pages (from-to)4141-4152
Number of pages12
JournalJournal of Theoretical and Applied Information Technology
Volume99
Issue number16
Publication statusPublished - 31-08-2021
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science

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