Diversity-based selection pooling scheme in evolution strategies
Proceedings of the 2001 ACM symposium on Applied computing
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PPSN VI Proceedings of the 6th International Conference on Parallel Problem Solving from Nature
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PPSN VI Proceedings of the 6th International Conference on Parallel Problem Solving from Nature
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Applied Mathematics and Computation
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GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
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ICCS'03 Proceedings of the 2003 international conference on Computational science
Assigning cells to switches in cellular mobile networks: a comparative study
Computer Communications
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The mutation-or-selection evolutionary strategy (MOSES) is presented. The goal of this strategy is to solve complex discrete optimization problems. MOSES evolves a constant sized population of labeled solutions. The dynamics employ mechanisms of mutation and selection. At each generation, the best solution is selected from the current population. A random binomial variable N which represents the number of offspring by mutation is sampled. Therefore the N first solutions are replaced by the offspring, and the other solutions are replaced by replicas of the best solution. The relationships between convergence, the parameters of the strategy, and the geometry of the optimization problem are theoretically studied. As a result, explicit parametrizations of MOSES are proposed