一种应用于柔性作业车间成组调度问题的分级优化算法

提出一种求解柔性作业车间成组调度FGJSS(flexible grouped job-shop scheduling)问题的蚁群粒子群求解算法。算法采用主从递阶形式,主级为蚁群优化算法,选择零件加工设备;从级为粒子群优化算法,在主级零件加工设备约束下优化设备作业排序以实现流通时间最小的目标。算法中,以工序加工时间和设备承载的作业族数为启发式信息设计蚂蚁在工序可用设备间转移概率;以粒子向量优先权值和作业族号为依据设计解码方法实现设备上的成组作业排序。最后,通过仿真实验,验证了该算法的有效性。

GRADED OPTIMISATION ALGORITHM APPLYING IN FLEXIBLE GROUPED JOB-SHOP SCHEDULING PROBLEMS

A hybrid algorithm of ant colony optimisation and particle swarm optimisation is proposed to solve the flexible grouped job-shop scheduling problem.The algorithm is formulated in a form of hierarchical master-slave structure.The ant colony optimisation is performed at master level to select equipments for parts machining,while the particle swarm optimisation is carried out at the slave level to optimise job-scheduling of the equipments in constrained condition of equipments for parts machining at master level to achieve the target of minimized circulation time.In the algorithm,the processing time of working procedure and the number of job groups the equipments loaded are used as the heuristic information to design the transfer probability of ant between the available machines of working procedure.The particle vector priority values and the jobs group number are employed as the base to design decoding method in order to implement grouped job scheduling of the equipments.In the end,the validity of the proposed algorithm is verified through simulative experiment.