针对汽车涂装生产的车辆路由调度问题,为降低涂装作业颜色切换次数及后续生产序列偏差,实现有限的资源内制造成本最低。基于涂装车间内具有多线性缓冲存储区的特点,以随机的待喷涂车辆集合为输入,建立以颜色切换次数最少及总装生产需求...针对汽车涂装生产的车辆路由调度问题,为降低涂装作业颜色切换次数及后续生产序列偏差,实现有限的资源内制造成本最低。基于涂装车间内具有多线性缓冲存储区的特点,以随机的待喷涂车辆集合为输入,建立以颜色切换次数最少及总装生产需求队列偏差最小为目标的MILP(mixed integer linear programming)模型,入库基于启发式规则,出库通过改进遗传算法求解,输出车辆路由调度方案。最后以某新能源汽车厂涂装车间为例,开发了一套路由调度系统,验证了所提出的多线性缓冲区联合调度方法,使得涂装切换成本下降80%左右,总装生产需求偏差成本下降10%左右。展开更多
This research provides academic and practical contributions. From a theoretical standpoint, a hybrid harmony search(HS)algorithm, namely the oppositional global-based HS(OGHS), is proposed for solving the multi-object...This research provides academic and practical contributions. From a theoretical standpoint, a hybrid harmony search(HS)algorithm, namely the oppositional global-based HS(OGHS), is proposed for solving the multi-objective flexible job-shop scheduling problems(MOFJSPs) to minimize makespan, total machine workload and critical machine workload. An initialization program embedded in opposition-based learning(OBL) is developed for enabling the individuals to scatter in a well-distributed manner in the initial harmony memory(HM). In addition, the recursive halving technique based on opposite number is employed for shrinking the neighbourhood space in the searching phase of the OGHS. From a practice-related standpoint, a type of dual vector code technique is introduced for allowing the OGHS algorithm to adapt the discrete nature of the MOFJSP. Two practical techniques, namely Pareto optimality and technique for order preference by similarity to an ideal solution(TOPSIS), are implemented for solving the MOFJSP.Furthermore, the algorithm performance is tested by using different strategies, including OBL and recursive halving, and the OGHS is compared with existing algorithms in the latest studies.Experimental results on representative examples validate the performance of the proposed algorithm for solving the MOFJSP.展开更多
文摘针对汽车涂装生产的车辆路由调度问题,为降低涂装作业颜色切换次数及后续生产序列偏差,实现有限的资源内制造成本最低。基于涂装车间内具有多线性缓冲存储区的特点,以随机的待喷涂车辆集合为输入,建立以颜色切换次数最少及总装生产需求队列偏差最小为目标的MILP(mixed integer linear programming)模型,入库基于启发式规则,出库通过改进遗传算法求解,输出车辆路由调度方案。最后以某新能源汽车厂涂装车间为例,开发了一套路由调度系统,验证了所提出的多线性缓冲区联合调度方法,使得涂装切换成本下降80%左右,总装生产需求偏差成本下降10%左右。
基金supported by the National Key Research and Development Program of China(2016YFD0700605)the Fundamental Research Funds for the Central Universities(JZ2016HGBZ1035)the Anhui University Natural Science Research Project(KJ2017A891)
文摘This research provides academic and practical contributions. From a theoretical standpoint, a hybrid harmony search(HS)algorithm, namely the oppositional global-based HS(OGHS), is proposed for solving the multi-objective flexible job-shop scheduling problems(MOFJSPs) to minimize makespan, total machine workload and critical machine workload. An initialization program embedded in opposition-based learning(OBL) is developed for enabling the individuals to scatter in a well-distributed manner in the initial harmony memory(HM). In addition, the recursive halving technique based on opposite number is employed for shrinking the neighbourhood space in the searching phase of the OGHS. From a practice-related standpoint, a type of dual vector code technique is introduced for allowing the OGHS algorithm to adapt the discrete nature of the MOFJSP. Two practical techniques, namely Pareto optimality and technique for order preference by similarity to an ideal solution(TOPSIS), are implemented for solving the MOFJSP.Furthermore, the algorithm performance is tested by using different strategies, including OBL and recursive halving, and the OGHS is compared with existing algorithms in the latest studies.Experimental results on representative examples validate the performance of the proposed algorithm for solving the MOFJSP.
