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Efficient hybrid methods for global continuous optimization based on simulated annealing
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- Miettinen, Kaisa, 1965- (author)
- Helsinki School of Economics
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- Mäkelä, Marko M. (author)
- Department of Mathematical Information Technology, University of Jyväskylä
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- Maaranen, Heikki (author)
- Department of Mathematical Information Technology, University of Jyväskylä
- (creator_code:org_t)
- Elsevier BV, 2006
- 2006
- English.
- In: Computers & Operations Research. - : Elsevier BV. - 0305-0548 .- 1873-765X. ; 33:4, s. 1102-1116
- Journal article (peer-reviewed)
Abstract
Subject headings
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- We introduce several hybrid methods for global continuous optimization. They combine simulated annealing and a local proximal bundle method. Traditionally, the simplest hybrid of a global and a local solver is to call the local solver after the global one, but this does not necessarily produce good results. Besides, using efficient gradient-based local solvers implies that the hybrid can only be applied to differentiable problems. We show several ways how to integrate the local solver as a genuine part of simulated annealing to enable both efficient and reliable solution processes. When using the proximal bundle method as a local solver, it is possible to solve even nondifferentiable problems. The numerical tests show that the hybridization can improve both the efficiency and the reliability of simulated annealing.
Subject headings
- NATURVETENSKAP -- Data- och informationsvetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences (hsv//eng)
Keyword
- Global optimization
- Metaheuristics
- Hybridization
- Bundle methods
Publication and Content Type
- ref (subject category)
- art (subject category)
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