Abstract
Many real life optimization problems are multimodal with multiple optima. Evolutionary Algorithms (EA) have successfully been used to solve these problems, but they have the disadvantage since that they converge to only one optimum, even though there are many optima. We proposed a hybrid algorithm combining differential evolution (DE) with tabu search (TS) to find multiple solutions of these problems. The proposed algorithm was tested on optimization problems with multiple optima and the results compared with those provided by the Particle Swarm Optimization (PSO) algorithm.
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References
Chelouah, R., Siarry, P.: A hybrid method combining continuous tabu search and Nelder-Mead simplex algorithms for the global optimization of multiminima functions. Eur. J. Oper. Res. 161, 636–654 (2005)
Das, S., Abraham, A., Chakraborty, U.K., Konar, A.: Differential evolution using a neighborhood based mutation operator. IEEE Trans. Evol. Comput. 13, 526–553 (2009)
Dorronsoro, B., Bouvry, P.: Improving classical and decentralized differential evolution with new mutation operator and population topologies. IEEE Trans. Evol. Comput. 15, 67–98 (2011)
Eberhart, R.C., Shi, Y.: Computational intelligence—concepts to implementations. Morgan Kaufmann, Burlington (2007)
Li, X.: Niching without niching parameters: particle swarm optimization using a ring topology. IEEE Trans. Evol. Comput. 14(1), 150–169 (2010)
Li, Z., Li, H., Chen, Y., Sallam, A.: A hybrid strategy based on niche genetic algorithm and tabu search and its convergence property, pp. 328–332. In: IEEE Fifth International Conference on Bio-Inspired computing: Theories and Applications (BIC-TA) (2010)
Mashinchi, M.H., Orgun, M.A., Pedrycz, W.: Hybrid optimization with improved tabu search. Appl. Soft Comput. 11, 1993–2006 (2011)
Storn, R., Price, K.V.: Differential evolution—a simple and efficient adaptive scheme for global optimization over continuous spaces. Technical Report TR-95-012. ICSI (1995)
Storn, R., Price, K.: Differential evolution—a simple and efficient heuristic for global optimization over continuous spaces. J. Global Optim. 11, 341–359 (1997)
Wei, L., Zhao, M.: A niche hybrid genetic algorithm for global optimization of continuous multimodal functions. Appl. Math. Comput. 160(3), 649–661 (2005)
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Schneider, E.R.F.A., Krohling, R.A. (2014). Differential Evolution and Tabu Search to Find Multiple Solutions of Multimodal Optimization Problems. In: Snášel, V., Krömer, P., Köppen, M., Schaefer, G. (eds) Soft Computing in Industrial Applications. Advances in Intelligent Systems and Computing, vol 223. Springer, Cham. https://doi.org/10.1007/978-3-319-00930-8_6
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DOI: https://doi.org/10.1007/978-3-319-00930-8_6
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