Equal size lot streaming to job-shop scheduling problem using genetic algorithms

Tung Sun Chan, T. C. Wong, P. L.Y. Chan

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

18 Citations (Scopus)

Abstract

A novel approach to solve Equal Size Lot Streaming (ESLS) in Job-shop Scheduling Problem (JSP) using Genetic Algorithms (GAs) is proposed. LS refers to a situation that a lot can be split into a number of smaller lots (or sub-lots) so that successive operation can be overlapped. By adopting the proposed approach, the sub-lot number for different lots and the processing sequence of all sub-lots can be determined simultaneously using GAs. Applying Just-In-Time (JIT) policy, the results show that the solution can minimize both the overall penalty cost and total setup time with the development of multi-objective function. In this connection, decision makers can then assign various weightings so as to enhance the reliability of the final solution.
Original languageEnglish
Title of host publicationIEEE International Symposium on Intelligent Control - Proceedings
Pages472-476
Number of pages5
Publication statusPublished - 1 Dec 2004
Externally publishedYes
EventProceedings of the 2004 IEEE International Symposium on Intelligent Control - 2004 ISIC - Taipei, Taiwan
Duration: 2 Sep 20044 Sep 2004

Conference

ConferenceProceedings of the 2004 IEEE International Symposium on Intelligent Control - 2004 ISIC
Country/TerritoryTaiwan
CityTaipei
Period2/09/044/09/04

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modelling and Simulation
  • Computer Science Applications
  • Electrical and Electronic Engineering

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