A Deterministic Algorithm for Global Optimization

Yury Evtushenko () and Mikhail Posypkin ()
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Yury Evtushenko: Institution of Russian Academy of Sciences Dorodnicyn Computing Centre of RAS
Mikhail Posypkin: Institution of Russian Academy of Sciences Dorodnicyn Computing Centre of RAS

A chapter in Managing Safety of Heterogeneous Systems, 2012, pp 205-218 from Springer

Abstract: Abstract An algorithm for solving global optimization problems is developed. The objective and constraints are required to have gradients satisfying Lipschitz condition. The problem may contain both continuous and integer variables and the objective may be non-convex and multimodal. Improved lower bounds and new techniques to reduce the number of algorithm steps by employing the gradient information are proposed for unconstrained optimization. Computational testing on different test problems demonstrate the efficiency of the proposed method in comparison with the state of the art approaches.

Keywords: Global Optimization; Lipschitz Constant; Unconstrained Optimization; Deterministic Algorithm; Global Optimization Problem (search for similar items in EconPapers)
Date: 2012
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Persistent link: https://EconPapers.repec.org/RePEc:spr:lnechp:978-3-642-22884-1_10

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DOI: 10.1007/978-3-642-22884-1_10

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