A hybrid genetic algorithm for twice continuously differentiable NLP problems
This paper introduces a new hybrid genetic algorithm to solve twice continuously differentiable nonlinear programming (NLP) problems. The algorithm combines the genetic algorithm with local solver differently from some hybrid genetic algorithms. Numerical experiments show the new hybrid genetic algorithm can obtain results better than the known ones reported by the literatures. (C) 2009 Elsevier Ltd. All rights reserved.
hybrid genetic algorithm twice continuously differentiable nlp local search global optimization