Hybridization of Differential Evolution using Hill Climbing to solve Constrained Optimization Problems

• Autores: Sebastián Hernández, Mario Guillermo Leguizamón, Efrén Mezura Montes
• Localización: Inteligencia artificial: Revista Iberoamericana de Inteligencia Artificial, ISSN-e 1988-3064, ISSN 1137-3601, Vol. 16, Nº. 52, 2013 (Ejemplar dedicado a: WASI), págs. 3-15
• Idioma: inglés
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• Resumen

  • Differential Evolution (DE) is a powerful metaheuristic method used to numerically optimize functions or multidimensional problems not solved by traditional methods of global optimization. In turn, if boundary conditions are added, constraint handling techniques should be need. To improve DE’s performance, algorithms of local search are a good alternative. Hybridization of Differential Evolution and Hill Climbing are presented in this paper. The obtained results show similar or superior quality to those achieved by methods already tested.