Optimization and Simulation for Designing the Supply Chain of the Cellulosic Biofuel Industry

The purpose of this dissertation is to provide an effective approach to design the supply chain (SC) of the cellulosic biofuel industry in order that it will support and accelerate the successful commercialization of the cellulosic biofuel industry. The methods of approach to this problem are (1) to assess the state-of-the-art biofuel SC studies, (2) to provide a decision support tool based on a mixed integer programming (MIP) model for the cellulosic biofuel supply chain design problem (BSCP), (3) to devise an exact solution method to solve large-scale instances of BSCP, (4) to evaluate a biomass logistics system based on biomass modules, by using new simulation elements for new machines, and (5) to compare several biomass logistics systems based on biomass module, bale, and silage, using simulation models.

The first part of this dissertation broadly reviews the literature on biofuel SCs, analyzing the state-of-the-art biofuel and petroleum-based fuel SC studies as well as relating generic SC models that have been published over the last decade to the biofuel SC (An et al., 2010a). The resulting analysis proposes fertile opportunity for future research to contribute to improving biofuel SC. The second part of this dissertation formulates BSCP as a MIP model, which is a time-staged, multi-commodity flow, network design problem with an objective of maximizing profit (An et al., 2010b). The model prescribes strategic level decisions (i.e., facility locations, capacities, and technology types) as well as plans for transportation routes and material flows (i.e., quantities produced, stored, and transported) in each time period. A case study demonstrates managerial use in application to a region in Central Texas.

The third part of this dissertation provides an exact solution method to solve BSCP. An embedded structure can be transformed to a generalized minimum cost flow problem, which is used as a sub-problem in a CG approach. This study proposes a dynamic programming algorithm to solve the sub-problem in O(m), generating improving path-flows. To accelerate branch-and-bound (B&B) search, it develops an inequality, called the partial objective constraint (POC), which is based on the portion of the objective function associated with binary variables.

The fourth part of this dissertation evaluates a biomass module system, which is a conceptual logistics system based on large packages of chopped biomass with sufficient size and density to provide maximized legal highway loads and quick load/unload times. The last part of this dissertation evaluates economic benefits of the biomass module system, comparing it to bale and silage systems.