基于蜂群算法的作业车间调度优化

Optimization in job shop scheduling based on wasp colony algorithm

基于蜂群的自组织自适应特征,构造了作业车间调度算法:摇尾舞算法和觅食算法.该算法利用蜂群与环境的交互模型来实现作业车间的动态调度,利用群体智能技术解决作业车间生产调度问题.仿真结果表明:该算法性能与蚁群算法相当,但离禁忌算法还有差距;该方法还能够起到优化调度的作用.

A new production scheduling with the characteristic of self-organization and adaptation is proposed, including waggle dance algorithm and forage algorithm. The swarm intelligence is adopted to present a novel dynamic job shop scheduling, where the model describing the interaction between the wasp colony and the environment is used to implement the dynamic scheduling. The experimental results show that in spite of the same effect as the ant algorithm, wasp colony algorithm still cant do as well as tabu search. The algorithm proposed is effective in job shop scheduling.