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

Abstract

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 2$12.9 to $99.2M/yr, and emit 791 ton CO 2 -eq/yr to 31,571 ton CO 2 -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. V C 2014 American Institute of Chemical Engineers AIChE J, 61: 530-554, 2015Green steps denote final solution steps, yellow denote checking steps, red steps denote that another iteration is needed, and blue denotes solving an MILP with the SOS1 formulation. UB 5 upper bound, LB 5 lower bound. [Color figure can be viewed in the online issue, which is available at wileyonlinelibrary.com.] 540Hardwood is converted via gasification and subsequent upgrading to gasoline. [Color figure can be viewed in the online issue, which is available at wileyonlinelibrary.com.]

Life Cycle Network Modeling Framework and Solution Algorithms for Systems Analysis and Optimization of the Water-Energy Nexus

“…In order to confront these difficulties, a novel solution algorithm is developed that can solve the problem more efficiently than general-purpose global optimization solvers. We implement a branch and refine algorithm [33,41] using piecewise linear approximations of the nonconvex capital cost terms paired with the parametric algorithm (in the case of a fractional objective function) and NLP subproblems of the original MINLFP problem to find valid lower and upper bounds on the objective. Eventually, the algorithm terminates with the globally optimal solution.…”

“…This difficulty can be addressed by introducing a branch and refine algorithm utilizing successive inner piecewise linear approximations to the original capital cost Equation (6) [33,41,43]. In this work, we use a branch-and-refine method that utilizes specially ordered set variables of type 1 (SOS1), as such methods have been shown to perform well and better than other, similar methods [43].…”

“…Much of the data collection strategy can be found in the author's previous work, including methods for extracting reference operating costs, capital costs, yields, and energy use [33]. Similar methods are employed to extract water consumption rate data corresponding to each technology's reference capacity.…”

Early‐stage evaluation of biorefinery processing pathways using process network flux analysis

“…Extending the aforementioned models by considering the energy demand of selected unit operations and technologies, several groups propose extended superstructure formulations analyzing in addition, e.g., the global warming potential or the overall process energy demand. [26][27][28][29][30] These formulations vary in their complexity as these input-output models are either generally valid for a process or specific for particular unit operations. 30 A subsequent heat integration is performed in the studies of Kokossis et al, 14 Tock et al 31 and Niziolek et al 32 In Martin et al 33 water integration is considered in addition to the process superstructure.…”

Multi-criteria decision making approaches for green supply chains: a review

“…Among non-deterministic models fuzzy set theory is most frequently applied to take uncertainty into account. Fuzzy set theory is used to take et al (2015), Gao and You (2015), Garcia and You (2015b), Garg et al (2015), Ghayebloo et al (2015), Kostin et al (2015), Mota et al (2015), Nagurney (2015), SantibanezAguilar et al (2015), Shimizu et al (2015), Tognetti et al (2015), Yu et al (2015), Yue et al (2015), Devika et al (2014), Govindan et al (2014a) 59 (38) 110 (19) 19 (8) 188 (65) a Publication with non-deterministic parameter(s)…”