混合流水车间多目标调度的小生境粒子群算法

Multi-Objective Problem of Schedule for Hybrid Flow Shop Based on Niching Particle Swarm Optimization

混合流水车间多目标调度问题(HFMSP)是一种具有很强应用背景的生产调度问题,对它的研究具有理论意义和工程价值。针对该类调度问题结合生产实际应用调度和多目标优化理论建立基于时间和交货期最优条件下的多目标调度问题模型,提出一种小生境粒子群算法对模型进行优化求解。该算法采用NSGA-II的非支配排序策略和动态加权方法选择最优粒子,利用粒子聚集距离的变异操作保证解的收敛性和多样性。通过仿真实验,验证了模型的正确性和算法的有效性。

Hybrid flow shop multi-objective scheduling problem is a kind of production scheduling problem in practical application. Study on it has theoretical significance and engineering value. For the scheduling problem, Combined with practical application scheduling and multi-objective optimization theory to estlish multi-objective scheduling model under satisfaction the time and date of delivery, a niche particle swarm algorithm is to put forward to optimize the model, The algorithm adopts the NSGA-II of the control strategy and dynamic weighted method selection to the optimal particle. It uses particle to gather the distance variation operation to ensure solution convergence and diversity. Through the simulation experiment it validates the model and illustrates the effectiveness of algorithm.