期刊名称：International Journal of Computer Science and Network Security
印刷版ISSN：1738-7906
出版年度：2019
卷号：19
期号：9
页码：216-222
出版社：International Journal of Computer Science and Network Security
摘要：This paper presents three hybrid algorithms, based on genetic algorithm (GA), to solve the generalized assignment problem (GAP) with the objective to minimize the assignment cost under the limitation of the agent capacity. First sequential constructive crossover (SCX) is modified for the problem and then showed competence over one-point crossover (OPX). Our hybrid algorithms use SCX, exchange mutation and three local search algorithms. Experimental results on four sets of benchmark instances from OR-library show the effectiveness of the proposed hybrid algorithms. The proposed algorithms are then compared with bee (BEE) and differential evolution (DE-SK) algorithms. In terms of solution quality as well as computational times, one of our hybrid genetic algorithm (HGA3) outperformed both BEE as well as DE-SK.
