Human-competitive lens system design with evolution strategies

Authors:
Christian Gagné;Julie Beaulieu;Marc Parizeau;Simon Thibault
Affiliations:
Laboratoire de Vision et Systèmes Numériques (LVSN), Département de Génie ílectrique et de Génie Informatique, Université Laval, Québec, Québec G1K 7P4 ...;Laboratoire de Vision et Systèmes Numériques (LVSN), Département de Génie ílectrique et de Génie Informatique, Université Laval, Québec, Québec G1K 7P4 ...;Laboratoire de Vision et Systèmes Numériques (LVSN), Département de Génie ílectrique et de Génie Informatique, Université Laval, Québec, Québec G1K 7P4 ...;ImmerVision, 2020 University, Montréal, Québec H3A 2A5, Canada
Venue:
Applied Soft Computing
Year:
2008

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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.