A genetic algorithm for unrelated parallel machine scheduling minimizing makespan cost and electricity cost under time-of-use (TOU) tariffs with job delay mechanism

B. Kurniawan, A. A. Gozali, W. Weng, Shigeru Fujimura

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

2 Citations (Scopus)

Abstract

Unrelated parallel machine scheduling under time-of-use electricity price is addressed in this paper. In this setting, price of electricity can be different among various periods of the day. The objective is to minimize total cost consisting of makespan cost and electricity cost. Genetic algorithm (GA) is used to solve the unrelated parallel machine scheduling under time varying tariffs. Chromosome decoding, inspired by greedy total cost, is proposed to transform individual into feasible schedule. Furthermore, generated schedule from the individual is improved by job delay mechanism that shifts jobs to other periods to avoid high electricity cost. Finally, numerical experiment is conducted to implement the approach. Preliminary result shows that our proposed approach is effective and efficient to solve the corresponding problem.

Original languageEnglish
Title of host publication2017 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2017
PublisherIEEE Computer Society
Pages583-587
Number of pages5
Volume2017-December
ISBN (Electronic)9781538609484
DOIs
Publication statusPublished - 2018 Feb 9
Event2017 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2017 - Singapore, Singapore
Duration: 2017 Dec 102017 Dec 13

Other

Other2017 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2017
CountrySingapore
CitySingapore
Period17/12/1017/12/13

Keywords

  • electricity cost
  • Genetic algorithm
  • makespan cost
  • time-of-use tariffs
  • unrelated parallel machine scheduling with job delay mechanism

ASJC Scopus subject areas

  • Business, Management and Accounting (miscellaneous)
  • Industrial and Manufacturing Engineering
  • Safety, Risk, Reliability and Quality

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  • Cite this

    Kurniawan, B., Gozali, A. A., Weng, W., & Fujimura, S. (2018). A genetic algorithm for unrelated parallel machine scheduling minimizing makespan cost and electricity cost under time-of-use (TOU) tariffs with job delay mechanism. In 2017 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2017 (Vol. 2017-December, pp. 583-587). IEEE Computer Society. https://doi.org/10.1109/IEEM.2017.8289958