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On decomposition and multiobjective-based column and disjunctive cut generation for MINLP
Most industrial optimization problems are sparse and can be formulated as block-separable mixed-integer nonlinear programming (MINLP) problems, defined by linking low-dimensional sub-problems by (linear) coupling constraints. This paper investigates the potential of using decomposition and a novel multiobjective-based column and cut generation approach for solving nonconvex block-separable MINLPs, based on the so-called resource-constrained reformulation. Based on this approach, two decomposition-based inner- and outer-refinement algorithms are presented and preliminary numerical results with nonconvex MINLP instances are reported.
On decomposition and multiobjective-based column and disjunctive cut generation for MINLP
Most industrial optimization problems are sparse and can be formulated as block-separable mixed-integer nonlinear programming (MINLP) problems, defined by linking low-dimensional sub-problems by (linear) coupling constraints. This paper investigates the potential of using decomposition and a novel multiobjective-based column and cut generation approach for solving nonconvex block-separable MINLPs, based on the so-called resource-constrained reformulation. Based on this approach, two decomposition-based inner- and outer-refinement algorithms are presented and preliminary numerical results with nonconvex MINLP instances are reported.
On decomposition and multiobjective-based column and disjunctive cut generation for MINLP
Optim Eng
Muts, Pavlo (Autor:in) / Nowak, Ivo (Autor:in) / Hendrix, Eligius M. T. (Autor:in)
Optimization and Engineering ; 22 ; 1389-1418
01.09.2021
30 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Decomposition method , Parallel computing , Column generation , Nonconvex optimization , Global optimization , Mixed-integer nonlinear programming Mathematics , Optimization , Engineering, general , Systems Theory, Control , Environmental Management , Operations Research/Decision Theory , Financial Engineering , Mathematics and Statistics
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