Research on flexible job shop scheduling with low-carbon technology based on quantum bacterial foraging optimization
INTERNATIONAL JOURNAL OF LOW-CARBON TECHNOLOGIES(2021)
摘要
In order to further reduce the carbon emission of manufacturing process in flexible job shop, a multi-objective integrated optimization model of flexible job-shop scheduling (FJSP) is proposed. A mathematics model is built in this paper to minimize makespan, total workload of machines and carbon emissions of machines and to optimize process method of each machine characteristic, process sequence and machine allocation. Considering many parameters are interactional and to be optimized in the proposed model, a quantum bacterial foraging optimization is designed to code the related parameters. On the basis of Kacem example through experimental simulation, the performance of the proposed method in the paper was analysed with ANOVA, and by comparing with the algorithms of current separated optimization method of process planning and scheduling, the effect of proposed integrated optimization model on reducing carbon emission in practical requirements of FJSP is verified.
更多查看译文
关键词
low carbon, flexible job-shop scheduling, quantum bacterial foraging optimization, ANOVA
AI 理解论文
溯源树
样例
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要