Evolutionary computation: toward a new philosophy of machine intelligence
Evolutionary computation: toward a new philosophy of machine intelligence
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
System Identification through Simulated Evolution: A Machine Learning Approach to Modeling
System Identification through Simulated Evolution: A Machine Learning Approach to Modeling
Genetic Algorithms and Simulated Annealing
Genetic Algorithms and Simulated Annealing
Evolutionary computation: comments on the history and current state
IEEE Transactions on Evolutionary Computation
A new mutation rule for evolutionary programming motivated frombackpropagation learning
IEEE Transactions on Evolutionary Computation
A novel stochastic optimization algorithm
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Cooperative mutation based evolutionary programming for continuous function optimization
Operations Research Letters
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A new fitness-based individual migration operator after the model of a migration phenomenon in a natural ecosystem is presented. The relative fitness variations are evaluated for each individual and those are used to determine whether an individual migrate to a new solution candidate which is far from its original position. This migration guarantees the search diversity by the uniformly dispersed individuals on a search space at the initial phase of evolution and fast convergence by the migrated individuals as the evolution progresses. The usefulness of the migration operator has been tested using evolutionary programming (EP) which adopts the operator. The performance of the proposed EP has been compared with those of other well-known EP algorithms through benchmark problems on continuous function optimization.