This paper presents a general optimization model that enables the selection of fuel conversion technologies, capacities, biomass locations, and the logistics of transportation from the locations of forestry resources to the conversion sites and then to the final markets. A mixed integer linear programming (MILP) model has been formulated and implemented in a commercial software package (GAMS) using databases built in Excel. The MILP represents decisions regarding (1) the optimal number, locations, and sizes of various types of processing plants, (2) the amounts of biomass, intermediate products, and final products to be transported between the selected locations over a selected period, and maximizes the objective function of overall profit. The model has been tested based on an industry-representative data set that contains information on the existing wood resources, final product market locations and demands, and candidate locations and sizes for different types of processing plants, as well as the costs associated with the various processing units and transportation of materials, covering the Southeastern region of the United States. The model is applied to design both a distributed, and a more centralized, conversion system. The overall profits, values, cost, and supply network designs of both systems are analyzed using the optimization model. In particular, we investigate: 1) which parameters have major effect on the overall economics, and 2) the benefits of going to more distributed types of processing networks, in terms of the overall economics and the robustness to demand variations. (C) 2010 Elsevier Ltd. All rights reserved.