On decomposition and multiobjective-based column and disjunctive cut generation for MINLP

被引：0
|
作者：
Pavlo Muts
Ivo Nowak
Eligius M. T. Hendrix
机构：
[1] Hamburg University of Applied Sciences,
[2] University of Malaga,undefined
来源：
Optimization and Engineering | 2021年 / 22卷
关键词：
Decomposition method; Parallel computing; Column generation; Nonconvex optimization; Global optimization; Mixed-integer nonlinear programming;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
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.
引用
收藏
页码：1389 / 1418
页数：29
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