APOGEE: Global optimization of standard, generalized, and extended pooling problems via linear and logarithmic partitioning schemes

被引:108
作者
Misener, Ruth [1 ]
Thompson, Jeffrey P. [1 ]
Floudas, Christodoulos A. [1 ]
机构
[1] Princeton Univ, Dept Chem & Biol Engn, Princeton, NJ 08544 USA
基金
美国国家科学基金会;
关键词
Large-scale optimization; Global optimization; MINLP; Quadratically constrained quadratic programs; Pooling problem; EPA Complex Emissions Model; WIDE WASTE MANAGEMENT; DIFFERENTIABLE CONSTRAINED NLPS; SUPERIOR REPRESENTATION METHOD; TRANSPORTATION FUEL DEMANDS; NATURAL-GAS PROCESSES; DISTILLATION SEQUENCES; WATER TREATMENT; NONCONVEX NLPS; HYBRID BIOMASS; ALGORITHM GOP;
D O I
10.1016/j.compchemeng.2011.01.026
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Our recent work globally optimized two classes of large-scale pooling problems: a generalized pooling problem treating the network topology as a decision variable and an extended pooling problem incorporating environmental regulations into constraints. The pooling problems were optimized using a piecewise linear scheme that activates appropriate under-and overestimators with a number of binary decision variables that scales linearly with the number of segments in the piecewise relaxation. Inspired by recent work (Vielma & Nemhauser, 2010; Vielma, Ahmed, & Nemhauser, 2010b), we introduce a formulation for the piecewise linear relaxation of bilinear functions with a logarithmic number of binary variables and computationally compare the performance of this new formulation to the best-performing piecewise relaxations with a linear number of binary variables. We have unified our work by developing APOGEE, a computational tool that globally optimizes standard, generalized, and extended pooling problems. APOGEE is freely available to the scientific community at helios.princeton.edu/APOGEE/. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码:876 / 892
页数:17
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