Multi-parametric disaggregation technique for global optimization of polynomial programming problems

João Teles, Pedro Castro () and Henrique Matos

Journal of Global Optimization, 2013, vol. 55, issue 2, 227-251

Abstract: This paper discusses a power-based transformation technique that is especially useful when solving polynomial optimization problems, frequently occurring in science and engineering. The polynomial nonlinear problem is primarily transformed into a suitable reformulated problem containing new sets of discrete and continuous variables. By applying a term-wise disaggregation scheme combined with multi-parametric elements, an upper/lower bounding mixed-integer linear program can be derived for minimization/maximization problems. It can then be solved to global optimality through standard methods, with the original problem being approximated to a certain precision level, which can be as tight as desired. Furthermore, this technique can also be applied to signomial problems with rational exponents, after a few effortless algebraic transformations. Numerical examples taken from the literature are used to illustrate the effectiveness of the proposed approach. Copyright Springer Science+Business Media, LLC. 2013

Keywords: Polynomial; Signomial; Optimization; Mixed-integer linear programming; Parameterization (search for similar items in EconPapers)
Date: 2013
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DOI: 10.1007/s10898-011-9809-8

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