An intelligent algorithm: MACO for continuous optimization models

Article type: Research Article

Authors: Zhu, Yuanguo

Affiliations: Department of Applied Mathematics, Nanjing University of Science and Technology, Nanjing, Jiangsu, China

Note: [] Corresponding author. Yuanguo Zhu, Department of Applied Mathematics, Nanjing University of Science and Technology, Nanjing, Jiangsu 210094, China. E-mail: [email protected]

Abstract: Ant colony optimization algorithm is a metaheuristic approach for the solutions of combinatorial optimization problems. In order to solve continuous optimization models, a new intelligent algorithm (MACO) combining a mutation ant colony optimization algorithm and a simulated annealing method is designed. Experiments and comparison with other metaheuristic methods by some test functions are shown the effectiveness of the proposed algorithm.

Keywords: Ant colony optimization, continuous optimization, metaheuristics, mutation, Metropolis' law

DOI: 10.3233/IFS-2012-0526

Journal: Journal of Intelligent & Fuzzy Systems, vol. 24, no. 1, pp. 31-36, 2013