Evolving artificial intelligence
Evolving artificial intelligence
New fitness-based migration operator for evolutionary programming
Neural, Parallel & Scientific Computations
An overview of evolutionary algorithms for parameter optimization
Evolutionary Computation
A new mutation rule for evolutionary programming motivated frombackpropagation learning
IEEE Transactions on Evolutionary Computation
Maximal age in randomized search heuristics with aging
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Experimental analysis of the aging operator for static and dynamic optimisation problems
KES'07/WIRN'07 Proceedings of the 11th international conference, KES 2007 and XVII Italian workshop on neural networks conference on Knowledge-based intelligent information and engineering systems: Part III
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In this letter an evolutionary programming (EP) algorithm adapting a new mutation operator is presented. Unlike most previous EPs, in which each individual is mutated on its own, each individual in the proposed algorithm is mutated in cooperation with the other individuals. This not only enhances convergence speed but also gives more chance to escape from local minima.