The research objective of this Faculty Early Career Development (CAREER) award is to investigate innovative optimization models and algorithms for problems in restoring supply chains after significant disruptive events, constructing supply chains to support humanitarian relief efforts, and transitioning supply chains to their next-generation redesign. These application areas have in common that the supply chain is operational as efforts are implemented to change its design. Therefore, the optimization models will focus on scheduling when and how the supply chain will change over time. In particular, limited resources will be allocated to perform tasks that change the characteristics of the components of the supply chain. The project's optimization models and algorithms specifically recognize the temporal aspects of the application areas and are innovative in the area of scheduling, since they focus on the interactions of the completed tasks within the supply chain. The educational program of this award will experiment with teaching methods that help to customize the learning experiences of engineering students based on their own interests and projected career paths.
If successful, the results of this research will provide tools that enable companies and organizations to propose and analytically assess strategies for their restoration, construction, and redesign efforts. This will help lessen the economical and societal impact of extreme events, since decision-makers in supply chain restoration and construction will be able to benchmark existing strategies and the impact of policy shifts in responding to the event. These tools will further help companies to understand how to integrate advanced manufacturing capabilities, including energy-efficient components, into their existing supply chains. The educational program will promote undergraduate research and develop new methods to better prepare students to apply optimization models in their projected career paths. These educational activities will help to promote the diversity of future options available to industrial engineering students.
