Optimization techniques for process synthesis and material design under uncertainty

被引：18

作者：

Dua, V ^{[1
]}

Pistikopoulos, EN ^{[1
]}

机构：

[1] Univ London Imperial Coll Sci Technol & Med, Dept Chem Engn, Ctr Proc Syst Engn, London SW7 2BY, England

来源：

CHEMICAL ENGINEERING RESEARCH & DESIGN | 1998年 / 76卷 / A3期

基金：

英国工程与自然科学研究理事会;

关键词：

parametric programming; process synthesis; material design;

D O I：

10.1205/026387698524839

中图分类号：

TQ [化学工业];

学科分类号：

0817 ;

摘要：

This paper describes developments in parametric mixed integer optimization for the solution of process synthesis and material design problems in the presence of uncertainty. For mixed integer linear models (MILP), such as the ones that arise in material design problems, a multiparametric MILP approach is described and illustrated with an example, whereas for mixed integer nonlinear convex models (MINLP), a parametric MINLP algorithm is presented and applied to a process synthesis example problem.

引用

页码：408 / 416

页数：9

共 41 条

[1] A parametric MINLP algorithm for process synthesis problems under uncertainty [J].