Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms
Niching methods for genetic algorithms
Niching methods for genetic algorithms
Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Intelligence
An Investigation of Niche and Species Formation in Genetic Function Optimization
Proceedings of the 3rd International Conference on Genetic Algorithms
An analysis of the behavior of a class of genetic adaptive systems.
An analysis of the behavior of a class of genetic adaptive systems.
Niching in evolution strategies
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Completely Derandomized Self-Adaptation in Evolution Strategies
Evolutionary Computation
The complete-basis-functions parameterization in ES and its application to laser pulse shaping
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Performance analysis of niching algorithms based on derandomized-ES variants
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Adaptive niche radii and niche shapes approaches for niching with the cma-es
Evolutionary Computation
Niche radius adaptation in the CMA-ES niching algorithm
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
IDEAL'06 Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning
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Evolutionary Algorithms (EAs), popular search methods for optimization problems, are known for successful and fast location of single optimal solutions. However, many complex search problems require the location and maintenance of multiple solutions. Niching methods, the extension of EAs to address this issue, have been investigated up to date mainly within the field of Genetic Algorithms (GAs), and their applications were limited to low-dimensional search problems. In this paper we present in detail the background for niching methods within Evolution Strategies (ES), and discuss two ES niching methods, which have been introduced recently and have been tested only for theoretical functions. We describe the application of those ES niching methods to a challenging real-life high-dimensional optimization problem, namely Femtosecond Laser Pulse Shaping. The methods are shown to be robust and to achieve satisfying results for the given problem.