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Genetic Programming for Job Shop Scheduling

  • Su NguyenEmail author
  • Mengjie Zhang
  • Mark Johnston
  • Kay Chen Tan
Chapter
First Online:
Part of the Studies in Computational Intelligence book series (SCI, volume 779)

Abstract

Designing effective scheduling rules or heuristics for a manufacturing system such as job shops is not a trivial task. In the early stage, scheduling experts rely on their experiences to develop dispatching rules and further improve them through trials-and-errors, sometimes with the help of computer simulations. In recent years, automated design approaches have been applied to develop effective dispatching rules for job shop scheduling (JSS). Genetic programming (GP) is currently the most popular approach for this task. The goal of this chapter is to summarise existing studies in this field to provide an overall picture to interested researchers. Then, we demonstrate some recent ideas to enhance the effectiveness of GP for JSS and discuss interesting research topics for future studies.

Keywords

Genetic programming Job shop scheduling Heuristic 
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Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  • Su Nguyen
    • 1
    Email author
  • Mengjie Zhang
    • 2
  • Mark Johnston
    • 3
  • Kay Chen Tan
    • 4
  1. 1.La Trobe UniversityBundooraAustralia
  2. 2.Victoria University of WellingtonWellingtonNew Zealand
  3. 3.University of WorcesterWorcesterUK
  4. 4.City University of Hong KongKowloon TongHong Kong

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