Recent Advances in Computational Models for the Discrete and Continuous Optimization of Industrial Process Systems

Abstract

An overview of the mathematical formulations used for discrete and continuous optimization are presented. These include Linear Programming, Nonlinear Programming, Integer Programming, Mixed-Integer Linear Programming, Mixed-Integer Nonlinear Programming, Logic-based Optimization, Stochastic Programming, Robust Optimization, and Flexibility Analysis. Successful applications of optimization models in industry are presented in the following fields: upstream oil & gas, materials blending, natural gas, biofuels, water treatment, electricity market integration, plant reliability, and supply chain design. Ongoing projects applying computational models to optimize industrial process systems are also mentioned. Implementations of customized optimization techniques that improve computational performance and enable finding solutions to otherwise unsolvable optimization problems are highlighted. These include strengthening cuts, decomposition strategies, model reformulation, and linearization, among others.