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Human-Competitive Lens System Design with Evolution Strategies


Christian Gagné, Julie Beaulieu, Marc Parizeau and Simon Thibault

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Abstract - Lens system design provides ideal problems for evolutionary algorithms: a complex non-linear optimization task, often with intricate physical constraints, for which there is no analytical solutions. This paper demonstrates, through the use of two evolution strategies, namely non-isotropic Self-Adaptive evolution strategy (SA-ES) and Covariance Matrix Adaptation evolution strategy (CMA-ES), as well as multiobjective Non-Dominated Sort Genetic Algorithm 2 (NSGA-II) optimization, the human competitiveness of an approach where an evolutionary algorithm is hybridized with a local search algorithm to solve both a classic benchmark problem, and a real-world problem.

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Bibtex:

@article{Gagné741,
    author    = { Christian Gagné and Julie Beaulieu and Marc Parizeau and Simon Thibault },
    title     = { Human-Competitive Lens System Design with Evolution Strategies },
    volume    = { 8 },
    number    = { 4 },
    pages     = { 1439-1452 },
    year      = { 2008 },
    month     = { September },
    journal   = { Applied Soft Computing },
    keywords  = { Lens design; Global optimization; Evolutionary computation; Evolution strategies; Multiobjective optimization; Memetic algorithm; Human competitiveness },
    web       = { http://dx.doi.org/10.1016/j.asoc.2007.10.018 }
}

Dernière modification: Sep 2 2008 12:01PM par cgagne

     
   
   

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