Determining a plant location is an important aspect of a firm's strategic and long-term investment planning. The costs associated with a plant include the high investment costs for its installment as well as its operational costs, which cover logistical costs for the upstream and downstream phases of the plant activity and are directly related to its geographical location [1-2]. In the energy supply chain network for the United States transportation sector, the location decision of fuel-producing plants will be affected by the locations and amounts of feedstock sources, locations and amounts of demands, and the infrastructure available to transport the plant's feedstock and products.
The high dependence on petroleum in the United States transportation sector has motivated research efforts to discover alternative sources and processes to fulfill the nation's demand. Gasification and Fischer-Tropsch based processes are among the promising alternatives due to its capability to convert and liquefy solid fuels such as coal and biomass, which are domestically more abundant. Recently, Baliban et al.  and Elia et al.  proposed a hybrid coal, biomass, and natural gas to liquid (CBGTL) process that has potential to satisfy the United States transportation demand, designed to produce gasoline, diesel, and kerosene in proportions that reflect the country's transportation requirements. Due to its unique feature, namely the CO2 recycle loop that allows a high feedstock-to-product carbon conversion, the process' economics is competitive with petroleum-based processes. In this work, we consider an energy supply chain problem to find the strategic CBGTL plant network suitable for the United States.
The CBGTL process is assessed to evaluate its environmental performance via a life-cycle analysis using the GREET model [5-6]. Since the transportation sector currently faces challenges to reduce the greenhouse gas emissions from the production, distribution, and consumption of liquid fuels, integrating biomass into fuel producing processes has been shown to show significant potentials to remediate this problem. As a renewable source, biomass can provide the negative carbon emissions during its growth and cultivation. Herbaceous energy crops, especially, can provide additional CO2 storage from soil sequestration [6-7]. There is, however, an upper limit to how much biomass can be utilized due to the land area constraint. By conducting a life cycle analysis for the CBGTL process, the amount biomass needed for the process to meet a certain emission target can be calculated.
We develop a mixed integer linear optimization model to find the discrete optimal locations such that the total network cost is minimized. Locations of biomass, coal, and natural gas sources are identified using published databases, and the corresponding amounts are adjusted such that the current usages of each feedstock are uninterrupted. The selection of the installed hybrid plants includes the decision on discrete locations, plant sizes, and feedstock types. Three different production plant sizes are considered, namely plants that produce 10,000, 50,000, and 200,000 barrels per day of liquid fuels (i.e., gasoline, diesel, and kerosene). Each plant is designed to receive one type of biomass, coal, and natural gas feedstock out of 6 possible coal types, 17 biomass types, and 1 natural gas. The biomass categories include herbaceous energy crops, agricultural and forest residues . An upper limit on natural gas carbon is set to be 15% of the total carbon input into the system, while the amounts of coal and biomass proportions are determined via a life-cycle analysis that sets a well-to-wheel emission target for each plant to be 50% of petroleum-based processes. This reduction is in accordance with the target to achieve 50% reduction in global emissions by 2050, as agreed by international leaders at the G8 summit . Finally, we compare the network topologies when the cost considered includes (i) only the transportation cost of feedstock delivery and the distribution of products, and (ii) the total investment costs of the system. We investigate how these topologies affect the price of the produced transportation fuels and the economic viability of the CBGTL energy supply network.
 Rentizelas, A.A., Tatsiopoulos, I.P., Locating a bioenergy facility using a hybrid optimization method. Int. J. Production Economics, 123:196-209, 2010.
 Lee, Y.H., Kwon, S.G., The hybrid planning algorithm for the distribution center operation using tabu search and decomposed optimization. Expert Systems with Applications, 37:3094-3103, 2010.
. Baliban, R.C., Elia, J.A., Floudas, C.A., Towards Novel Hybrid Biomass, Coal, and Natural Gas Processes for Satisfying Current Transportation Fuel Demands. Part I: Process Alternatives, Gasification Modeling, Process Simulation, and Economic Analysis. Submitted for publication, 2010.
 Elia, J.A., Baliban, R.C., Floudas, C.A., Towards Novel Hybrid Biomass, Coal, and Natural Gas Processes for Satisfying Current Transportation Fuel Demands. Part II: Simultaneous Heat and Power Integration. Submitted for publication, 2010.
 Argonne National Laboratory, GREET 1.8b, The Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation (GREET). Model (release September 2008), 2007.
 Larson, E.D., Fiorese, G., Liu, G., Williams, R.H., Kreutz, T.G., Consonni, S., Co-production of decarbonized synfuels and electricity from coal + biomass with CO2 capture and storage: an Illinois case study. Energy Environ. Sci., 3:28-42, 2010.
 Tilman, D., Hill, J., Lehman, C., Carbon-Negative Biofuels from Low-Input High-Diversity Grassland Biomass. Science, 314:1598-1600, 2006.
 Department of Energy and Department of Agriculture, Biomass as Feedstock for a Bioenergy and Bioproducts Industry: The Technical Feasibility of a Billion-Ton Annual Supply. Document Number: DOE/GO-102005-2135, 2005. http://www1.eere.energy.gov/biomass/publications.html, 2005.
 G8 Hokkaido Toyako Summit Leaders Declaration; G8; July 8, 2008; Ministry of Foreign Affairs of Japan.