改进CPSO算法在电子产品生产调度中的应用

Improved CPSO algorithm and application of the electronic production scheduling

为解决电子制造企业生产计划的调度问题,以总完工时间最小为优化目标,建立生产调度优化模型,采用改进混沌粒子群(CPSO)算法进行求解.该算法中引入一种叠加Logistic扰动的Tent算子,使得算法在迭代过程陷入局部最优时能够进入混沌搜索机制.该算法利用算子良好的均匀分布特性随机更新代表产品加工顺序的粒子位置向量,保证种群的多样性,减少出现早熟现象.利用标准测试算例与某电子制造企业生产调度实例,分别对所提出的改进算法和标准PSO算法进行对比.研究结果表明:改进算法在解的平均值和标准差上优于标准PSO算法,适用于解决实际生产调度问题.

To solve the scheduling problem of production plan in an electronic manufacturing enterprise,this paper took minimizing the total completion time as optimization objective,established the production scheduling optimizing model,and adopted the improved chaotic particle swarm optimization（CPSO） algorithm for solving the problem.The algorithm introduces one Tent operator of superposition Logistic,so as that the algorithm has access to chaotic searching mechanism when plunging in local optimum iterative process.This algorithm takes advantage of the operator＇s characteristics—sound uniform distribution—to update the particle position vector,which represents the product processing order,in order to assure the population diversity and to prevent prematurity.Based on the testing of benchmarks and the production scheduling example,the improved algorithm is compared with the standard PSO algorithm.The simulation results show that the improved algorithm can have better mean and standard deviation than the standard PSO algorithm,and is more suitable for settling the actual production scheduling issues.