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)


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
Number of pages7
ISBN (Print)9781424413393
Publication statusPublished - 1 Jan 2007
EventCEC 2007. IEEE Congress on Evolutionary Computation - Singapore, Singapore
Duration: 25 Sep 200728 Sep 2007


ConferenceCEC 2007. IEEE Congress on Evolutionary Computation


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

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