自适应蚁群算法在双向生产车间调度中的应用

An Adaptive Ant Colony Algorithm Applied to Bi-direction Job Shop Scheduling

本文将蚁群算法与双向调度算法结合,用以解决以生产周期和关键工件交货期为优化目标的车间作业调度问题。在传统的蚁群算法的基础上自适应调整挥发系数,ρ采用新的启发式信息——机床利用率来定义能见度函数ηij(t),采用了新的allowed表更新方式。最后通过仿真实验证实了本文的自适应蚁群算法在车间作业的双向调度中优于现在广泛采用的遗传算法。

We combine an ant colony algorithm with bi -direction scheduling algorithm to solve the job shop scheduling problem with the optimization aim of the makespan and deadline of critical jobs. Based on the traditional ant colony algorithm, we adjust the evaporation coefficientp adaptively, adopt new heuristic rules to define the visibility function ηij（t） and update table allowed in a different way. Besides, the adaptive ant algorithm is proved to be better than GA which is widely used nowadays in bi-direction scheduling of job shop schedule.