LI Yunlong, LUO Guofu, WEN Xiaoyu, et al. Flexible job shop scheduling in cloud manufacturing environment based on hybrid genetic algorithm[J]. Journal of Light Industry, 2020, 35(3): 99-108. doi: 10.12187/2020.03.012
Citation:
LI Yunlong, LUO Guofu, WEN Xiaoyu, et al. Flexible job shop scheduling in cloud manufacturing environment based on hybrid genetic algorithm[J]. Journal of Light Industry, 2020, 35(3): 99-108.
doi:
10.12187/2020.03.012
Flexible job shop scheduling in cloud manufacturing environment based on hybrid genetic algorithm
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College of Mechanical and Electrical Engineering/He'nan Provincial Key Laboratory of Intelligent Manufacturing of Mechanical Equipment, Zhengzhou University of Light Industry, Zhengzhou 450002, China
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Received Date:
2019-08-30
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Abstract
Aiming at the problem of idle time utilization and conflict of discrete processing equipment generated by flexible job shop scheduling in cloud manufacturing environment, a flexible job shop scheduling scheme in cloud manufacturing environment based on hybrid genetic algorithm was proposed.Under the premise of ensuring the smooth completion of workshop tasks, the residual capacity of the workshop was defined and then packaged and released to the cloud platform. Taking the minimum penalty total cost as the goal,combined with the actual situation of workshop production scheduling, the cloud order tasks were selected to process together, and the genetic variable neighborhood hybrid algorithm was used to solve the optimal scheduling sequence of cloud tasks, and the optimal scheduling scheme was formulated. The benchmark test results showed that the scheme realized the collaborative production of workshop production tasks and cloud platform tasks, and improved the enterprise's revenue and resource utilization.
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Proportional views
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