Date of Award
12-2014
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Legacy Department
Civil Engineering
Committee Chair/Advisor
Yongxi Huang
Committee Member
Yongxi Huang
Committee Member
Mashrur Chowdhury
Committee Member
C. Hsein Juang
Committee Member
Margaret Wiecek
Abstract
This dissertation aims at modeling sustainability of renewable fuel supply chain systems against emerging challenges. In particular, the dissertation focuses on the biofuel supply chain system design, and manages to develop advanced modeling framework and corresponding solution methods in tackling challenges in sustaining biofuel supply chain systems. These challenges include: (1) to integrate 'environmental thinking' into the long-term biofuel supply chain planning; (2) to adopt multimodal transportation to mitigate seasonality in biofuel supply chain operations; (3) to provide strategies in hedging against uncertainty from conversion technology; and (4) to develop methodologies in long-term sequential planning of the biofuel supply chain under uncertainties. All models are mixed integer programs, which also involves multi-objective programming method and two-stage/multistage stochastic programming methods. In particular for the long-term sequential planning under uncertainties, to reduce the computational challenges due to the exponential expansion of the scenario tree, I also developed efficient ND-Max method which is more efficient than CPLEX and Nested Decomposition method. Through result analysis of four independent studies, it is found that the proposed modeling frameworks can effectively improve the economic performance, enhance environmental benefits and reduce risks due to systems uncertainties for the biofuel supply chain systems.
Recommended Citation
Xie, Fei, "MODELING SUSTAINABILITY IN RENEWABLE ENERGY SUPPLY CHAIN SYSTEMS" (2014). All Dissertations. 1504.
https://open.clemson.edu/all_dissertations/1504
Included in
Civil Engineering Commons, Operations Research, Systems Engineering and Industrial Engineering Commons, Power and Energy Commons