Genetic Programming for Job Shop Scheduling

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)12_Chapter in an edited book (Author)peer-review

8 Scopus Citations
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Author(s)

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Detail(s)

Original languageEnglish
Title of host publicationEvolutionary and Swarm Intelligence Algorithms
EditorsJagdish Chand Bansal, Pramod Kumar Singh, Nikhil R. Pal
PublisherSpringer, Cham
Pages143-167
ISBN (Electronic)978-3-319-91341-4
ISBN (Print)978-3-319-91339-1
Publication statusPublished - 2019

Publication series

NameStudies in Computational Intelligence
Volume779
ISSN (Print)1860-949X
ISSN (Electronic)1860-9503

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.

Research Area(s)

  • Genetic programming, Heuristic, Job shop scheduling

Bibliographic Note

Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s).

Citation Format(s)

Genetic Programming for Job Shop Scheduling. / Nguyen, Su; Zhang, Mengjie; Johnston, Mark; Tan, Kay Chen.

Evolutionary and Swarm Intelligence Algorithms. ed. / Jagdish Chand Bansal; Pramod Kumar Singh; Nikhil R. Pal. Springer, Cham, 2019. p. 143-167 (Studies in Computational Intelligence; Vol. 779).

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)12_Chapter in an edited book (Author)peer-review