模糊交货期Flow-shop调度问题的改进微粒群算法

Improved PSO algorithm for flow shop scheduling problem with fuzzy delivery time

针对企业生产中由定单变化引起的具有模糊交货期性质的连续生产调度问题,提出一种改进的微粒群算法.通过对模糊交货期Flowshop调度问题的模糊机会约束设置惩罚函数,引入自适应变异和交叉等方法来改进算法,仿真结果表明算法具有较好的全局寻优和实用性,优于遗传算法和启发式算法.

Aiming at the influence of uncertain orders on the continuous production of manufacturing shop, an improved particle swarm optimization algorithm is presented to solve the flow shop scheduling problem with fuzzy delivery time. According to the restrictions of the problem, the improved PSO algorithm employs the pen- alty function, the self-adaptive mutation and crossover strategies, etc. The results of simulation indicate that the algorithm has excellent global performance and practicability, better than the genetic algorithm and the heuristic algorithm.