Journal
IEEE ACCESS
Volume 7, Issue -, Pages 68043-68059Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2019.2916468
Keywords
Energy-saving; flexible job shop scheduling; dual-resource; mixed integer linear programming; variable neighbourhood search
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Funding
- Funds for the National Natural Science Foundation of China [51575211, 51705263, 51875429]
- Project of International Cooperation and Exchanges NSFC [51861165202]
- Science and Technology Development Project of Jilin Province [20180101058JC]
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This paper addresses the dual-resource constrained flexible job shop scheduling problem (DRCFJSP) with minimizing energy consumption. It is the first to study the energy-conscious DRCFJSP with turn Off/On strategy. Different from the classical FJSP, the worker flexibility is considered in DRCFJSP. First, in order to solve this problem, we propose two mixed integer linear programming (MILP) models based on two modeling ideas, namely, idle time and idle energy. Because DRCFJSP is NP-hard, then we propose an efficient variable neighborhood search (VNS) algorithm. In the proposed VNS algorithm, eight neighborhood structures are designed to generate neighboring solutions. In addition, four energy-saving decoding approaches are specifically designed, in which two energy-saving strategies, namely, postponing strategy and turn Off/On strategy are designed. Finally, the MILP model, the energy-conscious decoding methods, and the VNS are evaluated on numerical tests, whose effectiveness is shown by the experimental results. The experimental results show that the MILP model based on idle energy performs better than the model based on idle time idea, and the greedy hybrid decoding method outperforms the other three decoding methods. Moreover, the proposed VNS with eight neighborhood structures is a very competitive algorithm for the energy-conscious DRCFJSP.
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