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多任务小批量流水线遗传算法仿真与实施
引用本文:蔡兰,郭顺生,王彬.多任务小批量流水线遗传算法仿真与实施[J].组合机床与自动化加工技术,2005(7):100-102.
作者姓名:蔡兰  郭顺生  王彬
作者单位:武汉理工大学,机电学院,武汉,430070
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.

关 键 词:生产调度  遗传算法  交货
文章编号:1001-2265(2005)07-0100-03
修稿时间:2005年1月4日

The Design and Application of Algorithm For Multitask Small Batch Flow-shop Genetic Algorithm Module
CAI Lan,GUO Shun-sheng,WANG Bin.The Design and Application of Algorithm For Multitask Small Batch Flow-shop Genetic Algorithm Module[J].Modular Machine Tool & Automatic Manufacturing Technique,2005(7):100-102.
Authors:CAI Lan  GUO Shun-sheng  WANG Bin
Abstract: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
Keywords:flow-shop  genetic algorithm  consignment
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