Decoupling linear and nonlinear regimes: an evaluation of efficiency for nonlinear multidimensional optimization

Christopher M. Cotnoir and Balša Terzić ()
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Christopher M. Cotnoir: Old Dominion University
Balša Terzić: Old Dominion University

Journal of Global Optimization, 2017, vol. 68, issue 3, No 9, 663-675

Abstract: Abstract Solving a large subset of multidimensional nonlinear optimization problems can be significantly improved by decoupling their intrinsically linear and nonlinear parts. This effectively decreases the dimensionality of the problem, reduces the search space and improves the efficiency of the optimization. This decoupled approach is generalized with mathematical formalism and its superiority over standard methods empirically verified and quantified on a couple of examples involving $$\chi ^2$$ χ 2 curve fitting to data.

Keywords: Multidimensional nonlinear optimization; Nonlinear chi-square fitting; Genetic algorithm (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/s10898-016-0480-y

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