A hybrid global optimization algorithm for non-linear least squares regression

Antanas Žilinskas () and Julius Žilinskas ()

Journal of Global Optimization, 2013, vol. 56, issue 2, 265-277

Abstract: A hybrid global optimization algorithm is proposed aimed at the class of objective functions with properties typical of the problems of non-linear least squares regression. Three components of hybridization are considered: simplicial partition of the feasible region, indicating and excluding vicinities of the main local minimizers from global search, and computing the indicated local minima by means of an efficient local descent algorithm. The performance of the algorithm is tested using a collection of non-linear least squares problems evaluated by other authors as difficult global optimization problems. Copyright Springer Science+Business Media, LLC. 2013

Keywords: Global optimization; Simplicial partition; Non-linear least squares (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (7)

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DOI: 10.1007/s10898-011-9840-9

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