Lot splitting under different job shop conditions

F.T.S. Chan, T.C. Wong, L.Y. Chan

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

6 Citations (Scopus)

Abstract

Lot splitting is defined as the process of splitting lots into smaller sub-lots such that successive operations of the same lot can be overlapped on distinct machines. Hence, the lead time of the lot can be possibly shortened. In this paper, a genetic algorithm-based approach is proposed to examine the lot splitting effect under different job shop conditions as defined by three parameters: processing time range, setup time and system congestion index. The experimental results suggest that lot splitting technique has a significant impact on job shop system with longer processing time and less due date tightness.
Original languageEnglish
Title of host publicationCEC 2007 IEEE Congress on Evolutionary Computation
PublisherIEEE
Pages4722-4728
Number of pages7
ISBN (Print)9781424413393
DOIs
Publication statusPublished - 1 Jan 2007
EventCEC 2007. IEEE Congress on Evolutionary Computation - Singapore, Singapore
Duration: 25 Sep 200728 Sep 2007

Conference

ConferenceCEC 2007. IEEE Congress on Evolutionary Computation
CountrySingapore
CitySingapore
Period25/09/0728/09/07

Keywords

  • lot splitting
  • job shop conditions
  • job shop scheduling
  • genetic algorithm-based approach
  • system congestion index
  • machine intelligence
  • lead time reduction

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