A multi-objective robust algal biofuel supply chain under uncertainty

Advisors: Reinaldo J. Moraga; Shi-Jie Chen.Committee members: Christine Nguyen; Ziteng Wang.Includes bibliographical references.Includes illustrations.Energy has historically been of great importance to the world. Depletion of fossil fuels, growing demand, global warming, and etc. have even accentuated this importance more. Amongst the biomass for production of biofuel which is one of the most promising renewable energy options, algae have been gaining a lot of attention in recent years. This thesis will propose a Biofuel Supply Chain Network Design for the development of algal biofuels. In order to do so, a Mixed Integer Linear Program will be created to design and optimize a biofuel supply chain from raw material procurement to biofuel distribution. Furthermore, a robust optimization method will be utilized to enable the model to cope with uncertainties of the biofuel supply chain. In addition, an environmental objective would be considered alongside an economic objective both of which are optimized by augmented [epsilon]-Constraint method to address issues such as global warming.M.S. (Master of Science

Environmental and Economic Optimization of Algal Biofuel Supply Chain with Multiple Technological Pathways

This article optimizes the design and configuration of algal biofuel supply chain networks (SCN) under economic and environmental objectives. Minimization of the total supply chain cost and the total life cycle greenhouse gas emission are the economic and environmental objectives, respectively. The SCN has been modeled by a multiobjective mixed integer linear programming approach which incorporates multiple production pathways and time periods, seasonality factors, water evaporation, recycling opportunities, and other major traits of the algal biofuel SCN. The model determines the optimal strategic and tactical level decisions of all SCN echelons. A fuzzy solution-based ε-constraint method has been utilized to obtain Pareto-optimal solutions that illustrate the trade-off between economic and environmental objectives. The performance of the model has been assessed in a case study carried out in seven states of the U.S which intends to develop the algal biofuel SCN from the year 2018 to the year 2024. Essential information with regard to the future of different technological pathways, relative importance of various supply chain factors, and sensitivity analysis has been discussed with respect to the case study results