Abi, S. and Benhala, B. and Bouyghf, H. and Fakhfakh, M. (2019) A Comparative Study between ACO and de Techniques by Numerical Functions Optimization. In: UNSPECIFIED.

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Abstract

Recently, the attraction of meta-heuristic techniques has increased due to their capability for solving complex optimization problems in various areas. This paper present a comparative study between two meta-heuristics techniques namely Ant Colony Optimization (ACO) and Differential Evolution (DE). In order to determine the best way to combine these two techniques in view of a successful hybridization. For that, the performances in term of convergence rate, robustness and computing time of these two techniques are evaluated using a benchmark of ten known test functions in the literature. © 2019 IEEE.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Uncontrolled Keywords: Artificial intelligence; Benchmarking; Evolutionary algorithms; Heuristic methods; Optimization, Ant Colony Optimization (ACO); Benchmark tests; Comparative studies; Complex optimization problems; Differential Evolution; Meta heuristics; Meta-heuristic techniques; Numerical functions, Ant colony optimization
Subjects: Computer Science
Divisions: SCIENTIFIC PRODUCTION > Computer Science
Depositing User: Administrateur Eprints Administrateur Eprints
Last Modified: 31 Jan 2020 15:45
URI: http://eprints.umi.ac.ma/id/eprint/2213

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