基于混合粒子群-NEH算法求解无等待柔性流水车间调度问题

Hybrid PSO-NEH algorithm for solving no-wait flexible flow shop scheduling problem

针对以最小化最大完工时间为目标的无等待柔性流水车间调度问题,提出了一种混合粒子群-NEH算法.该算法利用粒子群优化算法解决机器分配问题,并进行全局优化;利用改进的NEH算法确定工件加工顺序,并首次提出差值平移算法计算问题目标值.在算法求解过程中,通过不断对停滞粒子实行变异操作,避免粒子群陷入早熟收敛状态.基于典型算例的仿真实验,证明了所提算法求解该类问题的可行性和有效性.

To solve the no-wait flexible flow shop scheduling problem with makespan criterion, a hybrid approach which combined particle swarm optimization （PSO） algorithm with NEH algorithm was proposed. PSO algorithm was used to deal with machine assignment problem and implement the global optimization, while the improved NEH algorithm was employed to order the jobs and parallel mobile method based on the difference value was put forward to get the objective. In the processing of the algorithm, the premature convergence phenomenon was avoided by mutating the particles that were stagnant. Computational results based on the typical benchmark suites show that the proposed algorithm is feasible and effective.