Title
Anisotropic adaptive variance scaling for Gaussian estimation of distribution algorithm.
Abstract
Traditional Gaussian estimation of distribution algorithms (EDAs) are confronted with issues that the variable variances decrease fast and the main search direction tends to become perpendicular to the improvement direction of the fitness function, which reduces the search efficiency of Gaussian EDAs (GEDAs) and makes them subject to premature convergence. In this paper, a novel anisotropic adaptive variance scaling (AAVS) technique is proposed to improve the performance of traditional GEDAs and a new GEDA variant named AAVS-EDA is developed. The advantages of AAVS over the existing variance scaling strategies lie in its ability for tuning the variances and main search direction of GEDA simultaneously, which are achieved by anisotropically scaling the variances along different eigendirections based on corresponding landscape characteristics captured by a simple topology-based detection method. Besides, AAVS-EDA also adopts an auxiliary global monitor to ensure its convergence by shrinking all the variances if no improvement is achieved in a generation. The evaluation results on 30 benchmark functions of CEC2014 test suite demonstrate that AAVS-EDA possesses stronger global optimization efficiency than traditional GEDAs. The comparison with other state-of-the-art evolutionary algorithms also shows that AAVS-EDA is efficient and competitive.
Year
DOI
Venue
2018
10.1016/j.knosys.2018.02.001
Knowledge-Based Systems
Keywords
Field
DocType
Gaussian estimation of distribution algorithm,Premature convergence,Search direction,Anisotropic adaptive variance scaling
Convergence (routing),Data mining,Estimation of distribution algorithm,Evolutionary algorithm,Global optimization,Premature convergence,Computer science,Algorithm,Fitness function,Gaussian,Scaling
Journal
Volume
ISSN
Citations 
146
0950-7051
1
PageRank 
References 
Authors
0.37
27
6
Name
Order
Citations
PageRank
Zhigang Ren123819.86
Yongsheng Liang28412.98
Lin Wang352.16
Aimin Zhang4105.30
Bei Pang593.58
Biying Li610.37