Efficient and Accurate Parallel Genetic Algorithms
Efficient and Accurate Parallel Genetic Algorithms
ASPARAGOS An Asynchronous Parallel Genetic Optimization Strategy
Proceedings of the 3rd International Conference on Genetic Algorithms
Fine-Grained Parallel Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
Proceedings of the 5th International Conference on Genetic Algorithms
A Comparative Study of Global and Local Selection in Evolution Strategies
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
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
Parallelism and evolutionary algorithms
IEEE Transactions on Evolutionary Computation
The exploration/exploitation tradeoff in dynamic cellular genetic algorithms
IEEE Transactions on Evolutionary Computation
Selection intensity in cellular evolutionary algorithms for regular lattices
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Evolutionary Computation
Examining the Effect of Elitism in Cellular Genetic Algorithms Using Two Neighborhood Structures
Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X
Use of Local Ranking in Cellular Genetic Algorithms with Two Neighborhood Structures
SEAL '08 Proceedings of the 7th International Conference on Simulated Evolution and Learning
A Weighted Local Sharing Technique for Multimodal Optimisation
SEAL '08 Proceedings of the 7th International Conference on Simulated Evolution and Learning
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We implement a cellular genetic algorithm with two neighborhood structures following the concept of structured demes: One is for interaction among individuals and the other is for mating. The effect of using these two neighborhood structures on the search ability of cellular genetic algorithms is examined through computational experiments on function optimization problems. Experimental results show that good results are obtained from the combination of a small interaction neighborhood and a large mating neighborhood. This relation in the size of the two neighborhood structures coincides with many cases of biological evolution in nature such as plants and territorial animals. It is also shown that the search ability of cellular genetic algorithms is deteriorated by the opposite combination of the two neighborhood structures.