Graduation Year


Document Type




Degree Name

Doctor of Philosophy (Ph.D.)

Degree Granting Department

Industrial and Management Systems Engineering

Major Professor

Changhyun Kwon, Ph.D.

Co-Major Professor

Hadi Charkhgard, Ph.D.

Committee Member

Tapas K. Das, Ph.D.

Committee Member

Yujie Hu, Ph.D.

Committee Member

Yu Zhang, Ph.D.


conservation, food deserts, robust optimization, transportation, urban mobility, vehicle routing


This dissertation considers three separate optimization problems related to sustainable urban and environmental systems. The first problem relates to the nightly relocation and recharging operations for Free-floating electric vehicle sharing (FFEVS) systems. Such operations involve a crew of drivers to move the shared electric vehicles (EVs), and a fleet of shuttles to transport those drivers. Mixed integer programs are used to model the relocation and recharging operations. Two approaches are devised: sequential and synchronized approaches. In the sequential approach, the movement of EVs is first decided, then the routing of shuttles and drivers is determined. In the synchronized approach, all decisions are made simultaneously. To solve large-scale problems, an efficient computational method, called an exchange-based neighborhood-search method, is devised. The synchronized approach saves the total shuttle route up to 15% compared to the sequential approach. Important managerial insights related to operational resource allocation decisions are also presented. The second problem proposes using grocery deliveries to provide healthy foods to the food insecure population. To make the delivery financially viable, the problem considers consolidating customer orders and delivering to a neighborhood convenience store instead of home delivery. An optimization framework involving the minimum cost set covering and the capacitated vehicle routing problems is employed. The experimental studies in three counties in the U.S. suggest that by spatial and temporal consolidation of orders, the deliverer can remove minimum order-size requirements and substantially reduce the delivery costs, depending on various factors, compared to attended home-delivery. The final part of the dissertation considers

a robust optimization approach to problems in conservation planning that considers the uncertainty in data. Two of the basic formulations in conservation planning related to reserve selection and invasive species control are considered. Several novel techniques are developed to compare the results produced by the proposed robust optimization approach and the existing deterministic approach. Some numerical experiments are conducted to demonstrate the efficacy of the proposed approach in finding more applicable conservation planning strategies.