A global optimization method, alpha BB, for process design

被引：79

作者：

Adjiman, CS ^{[1
]}

Androulakis, IP ^{[1
]}

Maranas, CD ^{[1
]}

Floudas, CA ^{[1
]}

机构：

[1] PRINCETON UNIV, DEPT CHEM ENGN, PRINCETON, NJ 08544 USA

来源：

COMPUTERS & CHEMICAL ENGINEERING | 1996年 / 20卷

基金：

美国国家科学基金会;

关键词：

D O I：

10.1016/0098-1354(96)00080-4

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

A global optimization algorithm, alpha BB, for twice-differentiable NLPs is presented. It operates within a branch-and-bound framework and requires the construction of a convex lower bounding problem. A technique to generate such a valid convex underestimator for arbitrary twice-differentiable functions is described. The alpha BB has been applied to a variety of problems and a summary of the results obtained is provided.

引用

页码：S419 / S424

页数：6

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