Advertisement
Published in:
2013 | OriginalPaper | Chapter
100. Multi-Product Kanban System Based on Modified Genetic Algorithm
Author : Liang Huang
Published in: Proceedings of the International Conference on Information Engineering and Applications (IEA) 2012
Publisher: Springer London
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
Abstract
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.