NDLI: Research on improved genetic algorithm for low-dimensional and multimodal function optimization

Content Provider	IEEE Xplore Digital Library
Author	Liqing Xiao Huaxiang Wang Xiaoju Xu
Copyright Year	2011
Description	Author affiliation: School of Electrical Engineering & Automation, Tianjin University, Nankai District, Tianjin 300072, China (Liqing Xiao; Huaxiang Wang) \|\| Department of Information & Electrical Engineering, Xuzhou Institute of Technology, Xuzhou Jiangsu 221111, China (Xiaoju Xu)
Abstract	In order to overcome the disadvantages that simple genetic algorithm had in low-dimensional and multimodal function optimization, an improved algorithm was proposed. The new algorithm divided the search interval into different areas by method of orthogonal decomposition, produced initial populations that had different individual distribution density by using interval algorithm, and gave each individual an attribute that marked the area which it was in and guaranteed there was more than one individual in each area during the operating process of the algorithm. Particle swarm algorithm was introduced to the mutation operation of genetic algorithm to overcome the shortage of genetic algorithm, that was, the poor search ability in local areas, especially those that had low individual distribution density. When applied to six-hump camel back function and Branin RCOS function optimization, the simulation results show that, under the same experiment condition, in contrast to other improved algorithms, the new one improves the probability of searching to all extreme points, and has stronger ability of low-dimensional multi-modal function optimization, on the premise that the convergence precision is not affected.
Starting Page	3910
Ending Page	3914
File Size	233248
Page Count	5
File Format	PDF
ISBN	9781424487370
e-ISBN	9781424487387
DOI	10.1109/CCDC.2011.5968904
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-05-23
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Analytical models Interval Algorithm Six-hump Camel Back Function Simulation Branin RCOS Function Genetic Algorithm Particle swarm optimization Optimization Genetic algorithms Convergence Particle Swarm Algorithm
Content Type	Text
Resource Type	Article

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