多任务小批量流水线遗传算法仿真与实施  

The Design and Application of Algorithm For Multitask Small Batch Flow-shop Genetic Algorithm Module

作　　者：蔡兰[1] 郭顺生[1] 王彬[1] 

机构地区：[1]武汉理工大学机电学院,武汉430070

出　　处：《组合机床与自动化加工技术》2005年第7期100-102,共3页Modular Machine Tool & Automatic Manufacturing Technique

基　　金：国家重点攻关资助项目(2003BA103C)

摘　　要：文章阐述了在流水线调度时,可利用遗传算法计算出工件的最短通过时间,但这并非最佳方案,应同时考虑交货期的影响、设备的负荷率和员工加班等问题。在设计过程中,根据多任务,小批量流水线生产的特点,改进常规遗传算法,设计出一种基于交货期的遗传算法,可以很快地搜索到最优个体,并实例证明了其可行性。This paper introduces a method to design Job-shop scheduling module by using genetic algorithm, gains the least process time of workpieces . It is not the best method , in the same time, the infection of consignment time, the burthen of equipment and overtime should be considered. In the course of design, according to characteristic of multitask small-batch flow shop module, this paper improves the ordinary genetic algorithm and designs a optimization scheduling algorithm base on the consignment time. It's easy to find out optimum individual quickly. It also gives an example that proved it was feasible and effective approach method

关 键 词：生产调度 遗传算法 交货 

分 类 号：TH166[机械工程—机械制造及自动化] F273[经济管理—企业管理]