Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, 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
Completely Derandomized Self-Adaptation in Evolution Strategies
Evolutionary Computation
Performance analysis of derandomized evolution strategies in quantum control experiments
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Evolution strategies for laser pulse compression
EA'07 Proceedings of the Evolution artificielle, 8th international conference on Artificial evolution
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The Second Harmonic Generation (SHG), a process that turns out to be a good test case in the physics lab, can also be considered as a fairly simple theoretical test function for global optimization. Despite its symmetry properties, that will be derived here analytically, it seems to capture the complexity of the Fourier transform between the decision space to the evaluation space, and by that to challenge optimization routines. And indeed, counter-intuitively to some extent, locating its global maximum seems to be not an easy task for Evolutionary Algorithms (EAs). Although this research originates from the real-world applications domain, it aims to introduce a theoretical test case to Evolution Strategies (ES), being a possible theoretical gateway to the real-world physics regime of quantum control problems. After presenting some theoretical results, this paper introduces the study of the scalability of the decision space subject to optimization by specific variants of Derandomized Evolution Strategies. We show that the Evolution Strategy in use requires a quasi-quadratic increase of function evaluations for locating the global maximum as the dimensionality increases.