混沌微粒群算法在离散型生产调度中的应用

本文基于离散型生产调度问题的定义、约束条件,建立了相应的数学模型,针对微粒群算法后期容易陷入局部最优解且收敛速度慢的特点,提出了混沌的微粒群算法.详细介绍了混沌微粒群算法在离散型生产调度的优化流程,并将该算法用于实际项目,进行优化求解,与基本的微粒群算法对比得出更好的结果,验证了混沌微粒群算法的优越性.

Application of CPSO in Job-shop Scheduling

This paper firstly summarized the definition and constraints condition of Job-shop Scheduling Problem, established a relevant mathematics model. For the property that Particle Swarm Optimization Algorithm would easily sink into local extreme point and its slow convergence speed in later stage, Chaotic Particle Swarm Optimization（CPSO） was proposed to make up for this defect. This paper specifically introduced optimal process of CPSO in Job-shop Scheduling, and utilized the algorithm to calculate the actual project examples, which achieved the optimal solution. Compared to basic Particle Swarm Algorithm, it obtained the better result. After verification, CPSO had more advantages. The following illustrated the improvements.