Automatic design for shop scheduling strategies based on hyper-heuristics: A systematic review

Haoxin Guo, Jianhua Liu, Cunbo Zhuang*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

12 Citations (Scopus)

Abstract

Against the background of smart manufacturing and Industry 4.0, how to achieve real-time scheduling has become a problem to be solved. In this regard, automatic design for shop scheduling based on hyper-heuristics has been widely studied, and a number of reviews and scheduling algorithms have been presented. Few studies, however, have specifically discussed the technical points involved in algorithm development. This study, therefore, constructs a general framework for automatic design for shop scheduling strategies based on hyper-heuristics, and various state-of-the-art technical points in the development process are summarized. First, we summarize the existing types of shop scheduling strategies and classify them using a new classification method. Second, we summarize an automatic design algorithm for shop scheduling. Then, we investigate surrogate-assisted methods that are popular in the current algorithm field. Finally, current problems and challenges are discussed, and potential directions for future research are proposed.

Original languageEnglish
Article number101756
JournalAdvanced Engineering Informatics
Volume54
DOIs
Publication statusPublished - Oct 2022

Keywords

  • Classification of shop scheduling
  • Hyper-heuristic
  • Job shop
  • Scheduling strategy
  • Surrogate assisted

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