A New Energy-Aware Flexible Job Shop Scheduling Method Using Modified Biogeography-Based Optimization

作者：Zhang, Hua; Dai, Ziwei; Zhang, Wenyu^*; Zhang, Shuai; Wang, Yan; Liu, Rongyu

来源：Mathematical Problems in Engineering, 2017, 2017: 7249876.

DOI：10.1155/2017/7249876

• GENETIC ALGORITHM
• SEARCH ALGORITHM
• TIME
• CONSUMPTION
• ALLOCATION
• RESOURCES

Industry consumes approximately half of the total worldwide energy usage. With the increasingly rising energy costs in recent years, it is critically important to consider one of the most widely used energies, electricity, during the production planning process. We propose a newmathematicalmodel that can determine efficient scheduling to minimize the makespan and electricity consumption cost (ECC) for the flexible job shop scheduling problem (FJSSP) under a time-of-use (TOU) policy. In addition to the traditional two subtasks in FJSSP, a new subtask called speed selection, which represents the selection of variable operating speeds, is added. Then, a modified biogeography-based optimization (MBBO) algorithm combined with variable neighborhood search (VNS) is proposed to solve the biobjective problem. Experiments are performed to verify the effectiveness of the proposed MBBO algorithm for obtaining an improved scheduling solution compared to the basic biogeography-based optimization (BBO) algorithm, genetic algorithm (GA), and harmony search (HS).

• 出版日期2017
• 单位浙江财经大学