An efficient algorithm for convex multiparametric nonlinear programming problems

被引：19

作者：

Acevedo, J ^{[1
]}

Salgueiro, M ^{[1
]}

机构：

[1] ITESM Monterrey, Dept Chem Engn, Monterrey 64849, NL, Mexico

来源：

INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH | 2003年 / 42卷 / 23期

关键词：

D O I：

10.1021/ie0301278

中图分类号：

TQ [化学工业];

学科分类号：

0817 ;

摘要：

An efficient algorithm is proposed for the solution of multiparametric convex nonlinear problems (NLPs). Based on an outer-approximation algorithm, the proposed iterative procedure involves the solution of deterministic NLP subproblems and master multiparametric linear problems, with which an epsilon-approximate parametric solution profile can be defined. The procedure is guided by several heuristics that significantly reduce the number of primal subproblems solved and the complexity of the master problems. The applicability of the procedure is demonstrated through different variations of problems taken from the open literature, which serve to explain the algorithm in detail and compare its performance with those of previous approaches.

引用

页码：5883 / 5890

页数：8

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