Efficient and Accurate Parallel Genetic Algorithms
Efficient and Accurate Parallel Genetic Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary 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
Cellular Evolutionary Algorithms: Evaluating the Influence of Ratio
PPSN VI Proceedings of the 6th 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
How comma selection helps with the escape from local optima
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
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
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
Genetic Programming and Evolvable Machines
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Elitism has a large effect on the search ability of evolutionary algorithms. Many studies, however, did not discuss its different implementations in cellular algorithms. Usually a replacement policy called "replace-if-better" is applied to each cell in cellular algorithms as a kind of elitism. In this paper, we examine three implementations of elitism. One is global elitism where a prespecified number of the best individuals in the entire population are viewed as being the elite. The replace-if-better policy is applied only to the globally best individuals. Another scheme is local elitism where an individual is viewed as being the elite if it is the best among its neighbors. The replace-if-better policy is applied only to the locally best individuals. The other scheme is cell-wise elitism where the replace-if-better policy is applied to all individuals. Effects of elitism are examined through computational experiments using a cellular genetic algorithm with two neighborhood structures. One is for local competition among neighbors. This competition neighborhood is used in the local elitism to determine the locally best individuals. The other is for local selection of parents. This selection neighborhood is also called the mating neighborhood. Since we have the two neighborhood structures, we can specify the size of the competition neighborhood for the implementation of the local elitism independent of the selection neighborhood for mating. Experimental results show that the use of the replace-if-better policy at all cells is not always the best choice.