(573a) Sustainable Design of Supply Chains Using Life Cycle Optimization Framework Based On Functional Unit With Application On Hydrocarbon Biofuel Product Systems Conference: AIChE Annual MeetingYear: 2013Proceeding: 2013 AIChE Annual MeetingGroup: Computing and Systems Technology DivisionSession: Supply Chain Optimization II Time: Wednesday, November 6, 2013 - 3:15pm-3:35pm Authors: Yue, D., Northwestern University You, F., Cornell University Concerns about climate change, waste pollution, energy security and resource depletion are driving the society to explore a more sustainable way for development and manufacturing, which calls for sustainable thinking in design of product systems and supply chains under both economic and environmental concerns [1-3]. In this work, we propose the Life Cycle Optimization (LCO) framework for design and planning of general product systems and supply chains, which integrates classical Life Cycle Assessment (LCA) methodology and multi-objective optimization techniques [4-6]. Distinct from most works in this field, both objectives are modeled based on the functional unit, where all the costs and environmental footprints are embedded and reflected. In this way, we observe that further space for improvement in economic and environmental performances of the supply chain can be achieved, leading to more cost-competitive and environmentally green product systems. The multi-objective optimization framework is dealt with ε-constraint method, where the Pareto-optimal solutions are obtained by solving a sequence of subproblems with different ε-parameter values . Due to the presence of fractional economic and environmental objective functions regarding functional unit, the subproblems are formulated as mixed-integer linear fractional programming (MILFP) problems. To globally optimize the MILFPs effectively, we employ two tailored MILFP methods (specifically, parametric algorithm and reformulation-linearization method), which are shown to be much more efficient than general-purpose MINLP methods and global optimizers [8, 9]. To illustrate the application of the proposed modeling framework and solution methods, we investigate a county-level case study on the sustainable design of a potential hydrocarbon biofuel supply chain in the state of Illinois, consisting of 102 counties. Advanced hydrocarbon liquid transportation fuels derived from cellulosic biomass are considered promising renewable energy alternatives, of which the technologies are relatively mature. Therefore, the industry is eager for the development of corresponding supply chain and infrastructure [10, 11]. A spatially explicit model is formulated to integrate decision making across biomass acquisition, centralized-distributed conversion, and product distribution, meanwhile simultaneously predict the optimal network design, technology selection, capital investment, production operations and logistics management decisions. Gallon of gasoline-equivalent (GGE) is chosen as the functional unit for the hydrocarbon biofuel products, namely biomass-derived gasoline and diesel . The environmental performance is measured by the greenhouse gas (GHG) emission per GGE of biofuels, derived through a “field-to-wheel” LCA procedure based on the concept of 100-year global warming potentials (GWP100). The resulting Pareto solutions reveal the tradeoffs among the decision variables under both the economic and environmental objectives. 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