Hybrid Flowshop Scheduling using Leaders and Followers: An Implementation with Iterated Greedy and Genetic Algorithm

Tsung Su Yeh, Tsung Che Chiang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

A hybrid flow shop is a kind of flow shop where multiple machines are available at some stages. This paper addresses the hybrid flow shop scheduling problem (HFSP) with identical parallel machines. We propose an algorithm based on the framework of Leaders and Followers (LaF), a recent metaheuristic that searches by two populations. We apply iterated greedy (IG) to the leader population for exploitation and genetic algorithm (GA) to the follower population for exploration. Investigations on the parameter setting and technical details of the algorithm are made by experiments using 240 public problem instances. Performance comparison with two recent algorithms verifies the solution quality and computational efficiency of the proposed algorithm.

Original languageEnglish
Title of host publication2021 IEEE Symposium Series on Computational Intelligence, SSCI 2021 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728190488
DOIs
Publication statusPublished - 2021
Event2021 IEEE Symposium Series on Computational Intelligence, SSCI 2021 - Orlando, United States
Duration: 2021 Dec 52021 Dec 7

Publication series

Name2021 IEEE Symposium Series on Computational Intelligence, SSCI 2021 - Proceedings

Conference

Conference2021 IEEE Symposium Series on Computational Intelligence, SSCI 2021
Country/TerritoryUnited States
CityOrlando
Period2021/12/052021/12/07

Keywords

  • Flow shop
  • Leaders and followers
  • Metaheuristics
  • Parallel machines

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Decision Sciences (miscellaneous)
  • Safety, Risk, Reliability and Quality
  • Control and Optimization

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