Abstract-- In evolutionary algorithms, the fitness of a population increases with time by mutating and recombining individuals and by a biased selection of more fit individuals. Th...
Abstract. A model of coevolutioinary genetic algorithms (COGA) consisting of two populations coevolving on two-bit landscapes is investigated in terms of the effects of random par...
Ming Chang, Kazuhiro Ohkura, Kanji Ueda, Masaharu ...
A Quasi-Monte-Carlo method based on the computation of a surrogate model of the fitness function is proposed, and its convergence at super-linear rate 3/2 is proved under rather ...
Abstract. In this paper we propose a novel hybrid (GA/PSO) algorithm, Breeding Swarm, combining the strengths of particle swarm optimization with genetic algorithms. The hybrid alg...
This work presents a new approach to solve the location management problem by using the location areas approach. A combination of a genetic algorithm and the Hopfield neural netwo...