Please use this identifier to cite or link to this item: http://hdl.handle.net/10316/7724
Title: A particle swarm pattern search method for bound constrained global optimization
Authors: Vaz, A. 
Vicente, Luís 
Issue Date: 2007
Citation: Journal of Global Optimization. 39:2 (2007) 197-219
Abstract: Abstract In this paper we develop, analyze, and test a new algorithm for the global minimization of a function subject to simple bounds without the use of derivatives. The underlying algorithm is a pattern search method, more specifically a coordinate search method, which guarantees convergence to stationary points from arbitrary starting points. In the optional search phase of pattern search we apply a particle swarm scheme to globally explore the possible nonconvexity of the objective function. Our extensive numerical experiments showed that the resulting algorithm is highly competitive with other global optimization methods also based on function values.
URI: http://hdl.handle.net/10316/7724
DOI: 10.1007/s10898-007-9133-5
Rights: openAccess
Appears in Collections:FCTUC Matemática - Artigos em Revistas Internacionais

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