Genetic algorithms with sharing for multimodal function optimization
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms
Niching methods for genetic algorithms
Niching methods for genetic algorithms
Evolution strategies –A comprehensive introduction
Natural Computing: an international journal
An Investigation of Niche and Species Formation in Genetic Function Optimization
Proceedings of the 3rd International Conference on Genetic Algorithms
Proceedings of the 6th International Conference on Genetic Algorithms
Step-Size Adaption Based on Non-Local Use of Selection Information
PPSN III Proceedings of the International Conference on Evolutionary Computation. The Third Conference on Parallel Problem Solving from Nature: Parallel Problem Solving from Nature
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
A computational efficient covariance matrix update and a (1+1)-CMA for evolution strategies
Proceedings of the 8th annual conference on Genetic and evolutionary computation
On three new approaches to handle constraints within evolution strategies
Natural Computing: an international journal
Covariance Matrix Adaptation for Multi-objective Optimization
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
Mixed-Integer Evolution Strategies with Dynamic Niching
Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X
Enhancing Decision Space Diversity in Evolutionary Multiobjective Algorithms
EMO '09 Proceedings of the 5th International Conference on Evolutionary Multi-Criterion Optimization
Adaptive niche radii and niche shapes approaches for niching with the cma-es
Evolutionary Computation
Multimodal optimization by means of a topological species conservation algorithm
IEEE Transactions on Evolutionary Computation
Engineering Applications of Artificial Intelligence
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We introduce a framework of derandomized evolution strategies (ES) niching techniques. A survey of these techniques, based on 5 variants of derandomized ES, is presented, based on the fixed niche radius approach. The core mechanisms range from the very first derandomized approach to self-adaptation of ES to the sophisticatedMediaObjects/11047_2007_9065_Figa_HTML.gif Covariance Matrix Adaptation (CMA). They are applied to artificial as well as real-world multimodal continuous landscapes, of different levels of difficulty and various dimensions, and compared with the maximum-peak-ratio (MPR) performance analysis tool. While characterizing the performance of the different derandomized variants in the context of niching, some conclusions concerning the niching formation process of the different mechanisms are drawn, and the hypothesis of a trade-off between learning time and niching acceleration is numerically confirmed. Niching with (1 + λ)-CMA core mechanism is shown to experimentally outperform all the other variants, especially on the real-world problem. Some theoretical arguments supporting the advantage of a plus-strategy for niching are discussed. For the real-world application in hand, taken from the field of Quantum Control, we show that the niching framework can overcome some degeneracy in the search space, and obtain different conceptual designs using problem-specific diversity measurements.