A Novel Complex-Valued Encoding Grey Wolf Optimization Algorithm

A Novel Complex-Valued Encoding Grey Wolf Optimization Algorithm

Grey wolf optimization (GWO) is one of the recently proposed heuristic algorithms imitating the leadership hierarchy and hunting mechanism of grey wolves in nature. The aim of these algorithms is to perform global optimization. This paper presents a modified GWO algorithm based on complex-valued enc...

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Bibliographic Details
Main Authors: Qifang Luo, Sen Zhang, Zhiming Li, Yongquan Zhou
Format: Article
Language:English
Published: MDPI AG 2015-12-01
Series:Algorithms
Subjects:
complex-valued encoding
grey wolf optimization
diploid
test functions
IIR model identification
Online Access:http://www.mdpi.com/1999-4893/9/1/4
Description
Summary:Grey wolf optimization (GWO) is one of the recently proposed heuristic algorithms imitating the leadership hierarchy and hunting mechanism of grey wolves in nature. The aim of these algorithms is to perform global optimization. This paper presents a modified GWO algorithm based on complex-valued encoding; namely the complex-valued encoding grey wolf optimization (CGWO). We use CGWO to test 16 unconstrained benchmark functions with seven different scales and infinite impulse response (IIR) model identification. Compared to the real-valued GWO algorithm and other optimization algorithms; the CGWO performs significantly better in terms of accuracy; robustness; and convergence speed.
ISSN:1999-4893

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