First order rejection tests for multiple-objective optimization

Alexandre Goldsztejn (), Ferenc Domes () and Brice Chevalier ()

Journal of Global Optimization, 2014, vol. 58, issue 4, 653-672

Abstract: Three rejection tests for multi-objective optimization problems based on first order optimality conditions are proposed. These tests can certify that a box does not contain any local minimizer, and thus it can be excluded from the search process. They generalize previously proposed rejection tests in several regards: Their scope include inequality and equality constrained smooth or nonsmooth multiple objective problems. Reported experiments show that they allow quite efficiently removing the cluster effect in mono-objective and multi-objective problems, which is one of the key issues in continuous global deterministic optimization. Copyright Springer Science+Business Media New York 2014

Keywords: Multi-objective deterministic global optimization; First order optimality conditions; Interval analysis; Branch and bound algorithm; Cluster effect (search for similar items in EconPapers)
Date: 2014
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DOI: 10.1007/s10898-013-0066-x

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