Optimal Design of Sustainable Cellulosic Biofuel Supply Chains: Multiobjective Optimization Coupled with Life Cycle Assessment and Input-Output Analysis

TitleOptimal Design of Sustainable Cellulosic Biofuel Supply Chains: Multiobjective Optimization Coupled with Life Cycle Assessment and Input-Output Analysis
Publication TypeJournal Article
Year of Publication2011
AuthorsYou, F, Tao, L, Graziano, DJ, Snyder, S
JournalAIChE Journal
Date Published04/2011
Other NumbersANL/MCS-P1843-0211
Abstract

This paper addresses the optimal design and planning of cellulosic ethanol supply chains under economic, environmental, and social objectives. The economic objective is measured by the total annualized cost, the environmental objective is measured by the life cycle greenhouse gas emissions, and the social objective is measured by the number of accrued local jobs. A multiobjective mixed-integer linear programming (mo-MILP) model is developed that takes into account major characteristics of cellulosic ethanol supply chains, such as seasonality and geographical diversity of feedstock supply, biomass deterioration, feedstock density, diverse conversion technologies and byproducts, infrastructure compatibility, demand distribution, regional economic structure, and government incentives. Process models based on Aspen Plus for biorefineries with different feedstocks and conversion pathways are linked to the mo-MILP model for detailed techno-economic and environmental performance analysis. The proposed model simultaneously predicts the optimal network design, facility location, technology selection, capital investment, production planning, inventory control, and logistics management decisions. The mo-MILP problem is solved with an ε-constraint method; and the resulting Pareto-optimal curves reveal the tradeoff between the economic, environmental, and social dimensions of the sustainable biofuel supply chains. The proposed approach is illustrated through two case studies for the state of Illinois.

URLhttp://onlinelibrary.wiley.com/doi/10.1002/aic.12637/abstract
PDFhttp://www.mcs.anl.gov/papers/P1843B.pdf