Author:
Wen Ming Yue,Zhang Yi,Hu Fang Jun,Liu Zheng
Abstract
Cellular genetic algorithm (cGA) is a subclass of genetic algorithm (GA) in which the population diversity and exploration are enhanced thanks to the existence of small overlapped neighborhoods. Such a kind of structured algorithms is specially well suited for complex problems. Shop scheduling problem is a kind of problem with practical significance, and it belongs to a combinational optimization problem called NP-hard problem. In this paper we establish the model of job-shop problem (JSP) and solve the job-shop scheduling problem with cGA and traditional genetic algorithms (sGA).From the experimental results and analysis, we find cGA has better search efficiency and convergence performance than sGA.
Publisher
Trans Tech Publications, Ltd.
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