Multi-product Kanban system based on modified genetic algorithm

被引：0
作者：
Huang, Liang [1 ]
机构：
[1] Northeastern University at Qinhuangdao
来源：
Lecture Notes in Electrical Engineering | 2013年 / 219 LNEE卷 / VOL. 4期
关键词：
Genetic algorithm; Gradient-based heuristic; Kanban system; Simulation;
D O I：
10.1007/978-1-4471-4853-1_100
中图分类号：
学科分类号：
摘要：
Kanban system plays an important role in many manufacturing systems. The design of a Kanban system addresses the selection of two important parameters, i.e., the number of Kanbans and the lot size. This problem has been tackled in a number of studies using simulation models. But in the absence of an efficient gradient analysis method of the objective function, it is time-consuming in solving large-scale problems using a simulation model coupled with a meta-heuristic algorithm. In this chapter, a gradient-based heuristic is applied to a genetic algorithm for the design of a multi-product Kanban system. Several case studies in different sizes have been tried out and solutions from the modified genetic algorithm were compared to those from the classical genetic algorithm. Notable improvements in computing times or solutions by the modified genetic algorithm can be observed. © Springer-Verlag 2013.
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页码：817 / 824
页数：7
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