期刊
COMPLEXITY
卷 2020, 期 -, 页码 -出版社
WILEY-HINDAWI
DOI: 10.1155/2020/8565921
关键词
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资金
- National Natural Science Foundation of China [71840003]
- Science and Technology Development Program of the University of Shanghai for Science and Technology [2018KJFZ043]
- Ministry of Education Cloud Number Integration Science and Education Innovation Fund Project [2017A01109]
- Henan Province Science and Technology Research Project [182102210113]
Re-entrant hybrid flow shop scheduling problem (RHFSP) is widely used in industries. However, little attention is paid to energy consumption cost with the raise of green manufacturing concept. This paper proposes an improved multiobjective ant lion optimization (IMOALO) algorithm to solve the RHFSP with the objectives of minimizing the makespan and energy consumption cost under Time-of-Use (TOU) electricity tariffs. A right-shift operation is then used to adjust the starting time of operations by avoiding the period of high electricity price to reduce the energy consumption cost as far as possible. The experimental results show that IMOALO algorithm is superior to multiobjective ant lion optimization (MOALO) algorithm, NSGA-II, and MOPSO in terms of the convergence, dominance, and diversity of nondominated solutions. The proposed model can make enterprises avoid high price period reasonably, transfer power load, and reduce the energy consumption cost effectively. Meanwhile, parameter analysis indicates that the period of TOU electricity tariffs and energy efficiency of machines have great impact on the scheduling results.
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