改进离散粒子群算法求解柔性流水车间调度问题

针对以最小化完工时间为目标的柔性流水车间调度问题(FFSP),提出了一种改进离散粒子群(DPSO)算法.所提算法重新定义粒子速度和位置的相关算子,并引入编码矩阵和解码矩阵来表示工件、机器以及调度之间的关系.为了提高柔性流水车间调度问题求解的改进离散粒子群算法的初始群体质量,通过分析初始机器选择与调度总完工时间的关系,首次提出一种基于NEH算法的最短用时分解策略算法.仿真实验结果表明,该算法在求解柔性流水车间调度问题上有很好的性能,是一种有效的调度算法.

Improved discrete particle swarm algorithm for solving flexible flow shop scheduling problem

An improved Discrete Particle Swarm Optimization (DPSO) algorithm was proposed for solving the Flexible Flow Shop scheduling Problem (FFSP) with makespan criterion. The proposed algorithm redefined the operator of particle's velocity and position, and the encoding matrix and decoding matrix were introduced to represent the relationship between job, machine and scheduling. To improve the quality of initial population of the improved DPSO algorithm for the FFSP solution, by analyzing the relationship between the initial machine selection and the total completion time, a shortest time decomposition strategy based on NEH algorithm was proposed. The experimental results show that the algorithm has good performance in solving the flexible flow shop scheduling problem, and it is an effective scheduling algorithm.