关键词: 柔性流水车间, 调度算法, 粒子群, 模拟退火算法

Abstract: For the flexible flow shop scheduling (FFS) problem, this paper proposes a multi-search mechanism particle swarm optimization algorithm (MMPSO) in order to obtain a better optimal solution. Based on the analysis of the characteristics of flexible flow shop scheduling problem, this paper designs a particle information encoding scheme for the problem, then proposes the bottleneck machine elimination algorithm to improve the quality of initial population, while using NEH-Greedy search algorithm in the individual extremum search and SADA (simulated annealing disturb algorithm) search algorithm in all extremum search, which are both used to widen the search scope, improve the quality of feasible solutions and speed up the convergence process, in the iterative search RPA (random perturbation algorithm) operations are used to avoid plunging local optimum for all extremum. The experimental results show that the proposed algorithm can obtain a good optimal solution of this flexible flow shop scheduling problem by a faster convergence rate.

Key words: flexible flow shop, scheduling algorithm, particle swarm, simulated annealing algorithm