Flexible Job-Shop Scheduling Problem with Maintenance Activities Considering Energy Consumption

2014 ◽  
Vol 521 ◽  
pp. 707-713 ◽  
Author(s):  
Wen Jia Song ◽  
Chao Yong Zhang ◽  
Wen Wen Lin ◽  
Xin Yu Shao

With the developing of industry, the topic of energy-saving is attracting more and more attentions. However, the attentions have focused primarily on the design activities of the firm. The planning/scheduling activities of manufacturing are neglected. In this paper, a mathematical model, which considers the energy consumption and preventive maintenance of equipment in the flexible job shop, is established, three objectives, such as the minimization of maximum completion time, the minimization of total production energy costs and the minimization of total energy costs of maintenance that are quantized by electricity, are taken into account. The algorithm of NSGA-II is presented to solve the optimization model, and experimental results validate the effectiveness of the proposed approach.

2018 ◽  
Vol 32 (34n36) ◽  
pp. 1840112 ◽  
Author(s):  
Xiaoxing Zhang ◽  
Zhicheng Ji ◽  
Yan Wang

In this paper, a multi-objective flexible job shop scheduling problem (MOFJSP) was studied systematically. A novel energy-saving scheduling model was established based on considering makespan and total energy consumption simultaneously. Different from previous studies, four types of energy consumption were considered in this model, including processing energy, idle energy, transport energy, and turn-on/off energy. In addition, a turn-off strategy is adopted for energy-saving. A modified shuffled frog-leaping algorithm (SFLA) was applied to solve this model. Moreover, operators of multi-point crossover and neighborhood search were both employed to obtain optimal solutions. Experiments were conducted to verify the performance of the SFLA compared with a non-dominated sorting genetic algorithm with blood variation (BVNSGA-II). The results show that this algorithm and strategy are very effective.


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