基于粒子群算法的并行多机调度问题研究

Research on parallel machines scheduling problem based on particle swarm optimization algorithm

将港口拖轮作业调度问题描述为一类带特殊工艺约束的并行多机调度问题,采用粒子群算法求解该类调度问题,提出了一种2维粒子表示方法,通过对粒子位置向量进行排序生成有效调度,并采用粒子位置向量多次交换的局部搜索方法来提高算法的搜索效率。最后,通过计算验证了混合粒子群算法的有效性。

Port tugboat operation scheduling is regarded as parallel machines scheduling problem with special process constraint. Particle swarm optimization algorithm was used to solve the scheduling problem. The two-dimensional particle representation of parallel machines scheduling was proposed, and valid scheduling was generated by sequencing position vectors of particles. The local search approach of repeated interchanges of the particle position vectors was proposed to improve search efficiency. Finally the hybrid particle swarm algorithm was validated by computation.