Proceedings of the 5th International Conference on Genetic Algorithms
On Decentralizing Selection Algorithms
Proceedings of the 6th International Conference on Genetic Algorithms
An Analysis of the Effects of Neighborhood Size and Shape on Local Selection Algorithms
PPSN IV Proceedings of the 4th International Conference on Parallel Problem Solving from Nature
Spatially Structured Evolutionary Algorithms: Artificial Evolution in Space and Time (Natural Computing Series)
Anisotropic selection in cellular genetic algorithms
Proceedings of the 8th annual conference on Genetic and evolutionary computation
A fast hybrid genetic algorithm for the quadratic assignment problem
Proceedings of the 8th annual conference on Genetic and evolutionary computation
A study of NK landscapes' basins and local optima networks
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Cellular Genetic Algorithms
Selection intensity in asynchronous cellular evolutionary algorithms
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
Hierarchical cellular genetic algorithm
EvoCOP'06 Proceedings of the 6th European conference on Evolutionary Computation in Combinatorial Optimization
Selection intensity in cellular evolutionary algorithms for regular lattices
IEEE Transactions on Evolutionary Computation
Polynomial selection scheme with dynamic parameter estimation in cellular genetic algorithm
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Dynamic Fault-Tolerant three-dimensional cellular genetic algorithms
Journal of Parallel and Distributed Computing
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In this paper, we study the exploration / exploitation trade-off in cellular genetic algorithms. We define a new selection scheme, the centric selection, which is tunable and allows controlling the selective pressure with a single parameter. The equilibrium model is used to study the influence of the centric selection on the selective pressure and a new model which takes into account problem dependent statistics and selective pressure in order to deal with the exploration / exploitation trade-off is proposed: the punctuated equilibria model. Performances on the quadratic assignment problem and NK-Landscapes put in evidence an optimal exploration / exploitation trade-off on both of the classes of problems. The punctuated equilibria model is used to explain these results.