Parallel reactive tabu search for job-shop scheduling problems considering energy management

Shuhei Kawaguchi, Tatsuya Kokubo, Yoshikazu Fukuyama

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

1 Citation (Scopus)

Abstract

This paper presents parallel reactive tabu search for job-shop scheduling problems considering energy management. Production scheduling of factories should be minimized to keep customer delivery time. Since reduction of energy costs is important, operational planning of energy plants in factories should be optimized as well. However, the scheduling in factories and optimization of energy plants have been solved separately so far. Although energy costs have been ignored when the scheduling is optimized, it should be considered from the management point of view. This paper tries to optimize production scheduling and operational planning of energy plant simultaneously to minimize maximum end time of all factory operations (makespan) and total energy costs using parallel reactive tabu search.

Original languageEnglish
Title of host publication2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-8
Number of pages8
ISBN (Electronic)9781538627259
DOIs
Publication statusPublished - 2 Feb 2018
Event2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017 - Honolulu, United States
Duration: 27 Nov 20171 Dec 2017

Publication series

Name2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017 - Proceedings
Volume2018-January

Conference

Conference2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017
CountryUnited States
CityHonolulu
Period27/11/171/12/17

Keywords

  • combinatorial optimization problem
  • energy management systems
  • Job-shop scheduling problem
  • parallel reactive tabu search

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  • Cite this

    Kawaguchi, S., Kokubo, T., & Fukuyama, Y. (2018). Parallel reactive tabu search for job-shop scheduling problems considering energy management. In 2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017 - Proceedings (pp. 1-8). (2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017 - Proceedings; Vol. 2018-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SSCI.2017.8280877