多阶段可替换分组并行机调度的串行遗传算法  

Serial genetic algorithm for solving multi-stage alternative grouping parallel machines scheduling problem

作　　者：苗峰[1] 谢安桓[1] 王富安 喻峰 周华[1] 

机构地区：[1]浙江大学流体动力与机电系统国家重点实验室,杭州310027 [2]中国船舶重工集团第七〇七研究所九江分部,九江332007

出　　处：《现代制造工程》2015年第12期103-108,共6页Modern Manufacturing Engineering

摘　　要：针对一类多阶段可替换分组并行机混流生产调度问题,以最小化生产线工人总数和最小化订单提前期为目标建立了问题的数学模型,提出一种串行遗传算法;串行算法分步逐步确定最小的工人总数及其最优的工人配置,编码与生产线工人配置方案一一对应,采用包含多种规则的混合调度规则解码获得每阶段的调度方案,解码结果自动满足模型约束;算法采用改进的单点交叉算子和自适应种群规模,计算量小、求解速度快。针对不同规模的算例,仿真验证了算法的有效性。To solve the mixed flow scheduling problem with multi-stage alternative grouping parallel machines,the mathematical model to minimize the total number of production line workers and earliness time was constructed and a serial genetic algorithm was developed,the serial algorithm determines the minimum total number of workers and the optimal configuration of workers step by step. The coding method and configuration of workers is one-to-one correspondence. Scheduling scheme of each stage is determined by using the hybrid scheduling rules and the results will automatically satisfy model constraints. This algorithm has a small amount of calculation and high arithmetic speed with adaptive population size and modified one-point crossover. Simulation examples of different scales verify the effectiveness of the algorithm.

关 键 词：准时生产 多阶段 并行多机调度 调度规则 遗传算法 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] TP301.6[自动化与计算机技术—控制科学与工程]