Efficient hybrid methods for global continuous optimization based on simulated annealing
2006 (English)In: Computers & Operations Research, ISSN 0305-0548, Vol. 33, no 4, 1102-1116 p.Article in journal (Refereed) Published
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.
Place, publisher, year, edition, pages
2006. Vol. 33, no 4, 1102-1116 p.
Global optimization, Metaheuristics, Hybridization, Bundle methods
Computer and Information Science
IdentifiersURN: urn:nbn:se:kth:diva-83655DOI: 10.1016/j.cor.2004.09.005ISI: 000232998100013OAI: oai:DiVA.org:kth-83655DiVA: diva2:498877
QC 201202272012-02-122012-02-122012-02-27Bibliographically approved