An outer-approximation algorithm for the solution of multiparametric MINLP problems

作     者：Dua, V Pistikopoulos, EN 

作者机构：Univ London Imperial Coll Sci Technol & Med Ctr Proc Syst Engn Dept Chem Engn London SW7 2BY England 

出 版 物：《COMPUTERS & CHEMICAL ENGINEERING》 (计算机与化工)

年 卷 期：1998年第22卷第sup1期

页      面：S955-S958页

核心收录：

学科分类：0817[工学-化学工程与技术] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：process synthesis uncertainty mixed integer nonlinear programming parametric optimization 

摘      要：Process synthesis problems involving uncertainty can be mathematically represented as multiparametric mixed integer nonlinear programming(mp-MINLP) models. In this paper, we present an outer-approximation algorithm for the solution of such mp-MINLPs, described by convex process models, linear in the vectors of binary variables and uncertain parameters. The algorithm follows decomposition principles, i.e., constructing a converging sequence of valid upper and lower bounds through the solution of parametric primal and master subproblems. The solution is characterized in different sub-domains of the uncertain parameter space by (i) linear parametric profiles, and (ii) the corresponding integer solutions. (C) 1998 Elsevier Science Ltd. All rights reserved.