抄録
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.
本文言語 | English |
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ホスト出版物のタイトル | 2017 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2017 |
出版社 | IEEE Computer Society |
ページ | 583-587 |
ページ数 | 5 |
巻 | 2017-December |
ISBN(電子版) | 9781538609484 |
DOI | |
出版ステータス | Published - 2018 2 9 |
イベント | 2017 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2017 - Singapore, Singapore 継続期間: 2017 12 10 → 2017 12 13 |
Other
Other | 2017 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2017 |
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Country | Singapore |
City | Singapore |
Period | 17/12/10 → 17/12/13 |
ASJC Scopus subject areas
- Business, Management and Accounting (miscellaneous)
- Industrial and Manufacturing Engineering
- Safety, Risk, Reliability and Quality