Performance Analyses of Differential Evolution Algorithm Based on Dynamic Fitness Landscape

Author:

Li Kangshun1,Liang Zhuozhi1,Yang Shuling2,Chen Zhangxing3,Wang Hui1,Lin Zhiyi4

Affiliation:

1. South China Agricultural University, Guangzhou, China

2. South China University of Technology, Guangzhou, China

3. University of Calgary, Calgary, Canada

4. Guangdong University of Technology, Guangzhou, China

Abstract

Dynamic fitness landscape analyses contain different metrics to attempt to analyze optimization problems. In this article, some of dynamic fitness landscape metrics are selected to discuss differential evolution (DE) algorithm properties and performance. Based on traditional differential evolution algorithm, benchmark functions and dynamic fitness landscape measures such as fitness distance correlation for calculating the distance to the nearest global optimum, ruggedness based on entropy, dynamic severity for estimating dynamic properties, a fitness cloud for getting a visual rendering of evolvability and a gradient for analyzing micro changes of benchmark functions in differential evolution algorithm, the authors obtain useful results and try to apply effective data, figures and graphs to analyze the performance differential evolution algorithm and make conclusions. Those metrics have great value and more details as DE performance.

Publisher

IGI Global

Subject

Artificial Intelligence,Human-Computer Interaction,Software

Reference23 articles.

1. Analysing the fitness landscape of search-based software testing problems.;A.Aleti;Automated Software Engineering,2016

2. Climbing combinatorial fitness landscapes

3. Bolshakov, V., Pitzer, E., & Affenzeller, M. (2011). Fitness Landscape Analysis of a Simulation Optimisation Problems with HeuristicLab.

4. Branke, J. (2001). Evolutionary Optimization in Dynamic Environments,

5. De Jong, K. A. (1975). An Analysis of the Behavior of a Class of Genetic Adaptive Systems.

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