PhD Oral Defense: Spatial and temporal optimization of advanced biofuel supply chains in the United States: an integrated platform
PhD Oral Defense of Mohamed Laila, Department of Bioresource Engineering
Biofuels are one of the promising energy alternatives to reduce fossil fuel consumption and combat climate change. Growing civilian and military interest in acquiring cost competitive biofuels have inspired research to develop models that optimize their supply chains. Such models are constrained by several factors, namely the time-consuming data collection and processing, the complexity of formulating a mathematical optimization model, the need to use proprietary solvers, and the requirement for computational resources. To overcome these hurdles, researchers proposed the development of integrated platforms that streamline the described activities and enhance the accessibility to the required algorithms and hardware. Hence , the objectives of this thesis were to 1) formulate deterministic and stochastic mathematical optimization models to optimize biofuel supply chains in a spatially and
temporally explicit manner, and test their resilience under uncertainty, 2) design a web-based platform that integrates the proposed model with Application Program Interfaces and publicly available databases to construct user-defined case studies and solve optimization problems on third-party cloud servers, and 3) demonstrate the abilities of the platform
using a set of case studies of military biofuel supply chains in the Pacific region of the United States. The integrated platform is called the Biofuel supply chain Geospatial and Temporal Optimizer (BioGeSTO).