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Empirical Evidences to Validate the Performance of Self-Switching Base Vector Based Mutation of Differential Evolution Algorithm

Publication Type : Conference Paper

Publisher : International Conference on Advances in Computing, Communications and Informatics

Source : 2018 International Conference on Advances in Computing, Communications and Informatics (ICACCI) (2018)

Url : https://ieeexplore.ieee.org/document/8554928

Keywords : Base Vector, Benchmark testing, DE algorithm, Differential Evolution, differential evolution algorithm, EAs, Evolutionary algorithms, evolutionary computation, evolutionary computing field, History, Mutation strategy, optimisation, Optimization, Optimization problems, Population Diversity, self-switching base vector based mutation, self-switching base vector selection base mutation scheme, sociology, Statistics, Tools, Vectors

Campus : Coimbatore

School : School of Engineering

Department : Computer Science

Year : 2018

Abstract : There exist many tools in Computer Science to solve the optimization problems around us. One such tool is the set of algorithms known as Evolutionary Algorithms (EAs) which is under the Evolutionary Computing (EC) field. The Differential Evolution (DE) algorithm in the set of EAs is known for its unique mutation scheme. There are many research works in the literature to further study and modify this scheme to propose new mutation schemes. This paper presents detailed and extensive empirical evidences for the Self-Switching Base Vector Selection base mutation scheme (termed as DE/randorbest/1) found in the literature. The results for our validation are obtained by running the DE algorithm for all possible values of its control parameters (Mutation Step Size (F) and Crossover Rate (Cr)) on a Benchmarking-Function suite. The obtained results are compared by the performance metrics: Average Solution Accuracy (ASA) and Success Rate (SR).

Cite this Research Publication : K. Gokul, Pooja, R., and Dr. Jeyakumar G., “Empirical Evidences to Validate the Performance of Self-Switching Base Vector Based Mutation of Differential Evolution Algorithm”, in 2018 International Conference on Advances in Computing, Communications and Informatics (ICACCI), 2018.

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