摘要
研究了一种两层生产计划集成问题,上层为能力约束批量计划问题,下层为并行双机调度问题。采用单个模型来描述整个集成问题,目标函数由库存费用、缺货费用和加班费用三部分组成。对于该集成优化问题,设计了遗传算法整体求解,每个个体中同时包含了批量计划和作业排序的信息,并通过遗传算子的设计,避免了不可行解的出现。通过数值仿真实验,对三种不同规模的问题进行了计算,通过对计算结果的分析,验证了遗传算法的可行性和有效性。
An integrated problem was studied for a two-stage production planning, in which the upper-stage was a capacitated lot sizing problem and the lower-stage was a parallel two-machine scheduling problem. A single model was proposed to describe the whole problem. The objective of the model consists of three parts： the inventory cost, the shortage cost and the overtime cost. A genetic algorithm was designed to solve this problem based on monolithic method, within which every individual contained all the information of lot sizing and scheduling, and the infeasible solutions were avoided through the design of genetic operator. Numerical simulations were conducted, including the computation of three different sizes and the analysis of solutions. The result shows the feasibility and validity of our genetic algorithm.
出处
《系统仿真学报》
EI
CAS
CSCD
北大核心
2007年第16期3643-3649,共7页
Journal of System Simulation
基金
国家自然科学基金资助项目(70371005
70521001)
新世纪优秀人才支持计划资助(NCT040175)
关键词
多层生产计划
能力约束批量计划
并行机调度
遗传算法
multi-stage production planning
capacitated lot sizing problem
parallel machine scheduling
GA
