Multiobjective optimization of product and process networks: General modeling framework, efficient global optimization algorithm, and case studies on bioconversion

A comprehensive optimization model that can determine the most cost-effective and environmentally sustainable production pathways in an integrated processing network is needed, especially in the bioconversion space. We develop the most comprehensive bioconversion network to date with 193 technologies and 129 materials/compounds for fuels production. We consider the tradeoff between scaling capital and operating expenditures (CAPEX and OPEX) as well as life cycle environmental impacts. Additionally, we develop a general network-based modeling framework with nonconvex terms for CAPEX. To globally optimize the nonlinear program with high computational efficiency, we develop a specialized branch-and-refine algorithm based on successive piecewise linear approximations. Two case studies are considered. The optimal pathways have profits from -$12.9 to $99.2M/yr, and emit 791 ton CO₂-eq/yr to 31,571 ton CO₂-eq/yr. Utilized technologies vary from corn-based fermentation to pyrolysis. The proposed algorithm reduces computational time by up to three orders of magnitude compared to general-purpose global optimizers.