摘要
针对同时考虑顺序相关调整时间和运输时间等多时间因素的绿色可重入混合流水车间调度问题(GRHFSP-MTF),以最小化最大完工时间和总能耗为目标建立双目标优化模型。针对GRHFSP-MTF的特点,提出一种混合文化基因算法(HMA)。首先,提出了基于工序、机器和转速的三层编码策略;然后,设计了基于贪婪机器选择和完全随机的种群初始化方法、交叉和变异算子以及5种邻域搜索算子;最后,在不改变机器分配和工件排列的前提下,基于降低机器转速手段设计了节能算子。大量仿真实验表明,HMA可以有效地求解考虑多时间因素的绿色可重入混合流水车间调度问题,并具有较强的优越性。
For the Green Re-entrant Hybrid Flow Shop Scheduling problem with Multiple Time Factors(GRHFSP-MTF), such as sequence dependent adjustment time and transportation time, a bi-objective optimization model was built to minimize the maximum completion time and total energy consumption simultaneously. According to the characteristics of GRHFSP-MTF, a Hybrid Memetic Algorithm(HMA) was proposed. A three-layer coding strategy based on operations, machines and speeds was proposed. Then, a population initialization method based on greedy machine selection and complete random, crossover and mutation operators and five neighborhood search operators were designed. The energy saving operator was designed based on the method of reducing machining speed without changing machines allocation and jobs arrangement. Simulation experiments showed that the proposed HMA algorithm could effectively solve the green reentrant hybrid flow-shop scheduling problem considering multiple time factors, and had strong advantages.
作者
耿凯峰
叶春明
GENG Kaifeng;YE Chunming(School of Business,University of Shanghai for Science and Technology,Shanghai 200093,China;Information Construction and Management Center,Nanyang Institute of Technology,Nanyang 473004,China)
出处
《计算机集成制造系统》
EI
CSCD
北大核心
2023年第1期75-90,共16页
Computer Integrated Manufacturing Systems
基金
国家自然科学基金资助项目(71840003)
上海理工大学科技发展基金资助项目(2018KJFZ043)
2018年度河南省科技攻关资助项目(182102210113)。
关键词
可重入混合流水车间调度
绿色调度
顺序相关调整时间
运输时间
多时间因素
re-entrant hybrid flow shop scheduling
green scheduling
sequence dependent setup times
transportation time
multiple time factors
