Start date: 01/01/16
End date: 12/31/16
James F. Campbell
Management Science and Information Systems | University of Missouri-St. Louis
- Donald C. Sweeney II | firstname.lastname@example.org | University of Missouri - St. Louis
About the research
Our research develops strategic models for the design of truck-drone hybrid delivery systems using continuous approximation modeling techniques. These modeling techniques can provide valuable managerial insights by analyzing a general version of the delivery problem where the demand for deliveries is treated as a continuous density over a service region, rather than a unique discrete set of stops. The key issue for a strategic analysis is how best to utilize drones in conjunction with trucks.
Because drones have very different operating characteristics than trucks, and different types of drones exist, our modeling framework will be flexible to accommodate different types of drones, as well as different delivery systems. Some key operating parameters for drones include speed, capacity (payload), battery life, costs, and range. These characteristics are not independent, as for example greater speeds produce larger ranges, but decrease battery life. Generic models will be developed to clearly identify the impact of these key parameters on the design of the delivery system.
Two objectives will be modeled in designing the system: minimize the total cost for the truck-drone deliveries and minimize the total time to make all deliveries. Fixed and variable costs will be modeled for the trucks and drones, with the models including the inter-relationships of the key operating characteristics (e.g., speed, battery life/cost and delivery range). The nature of the demand will also be varied, both in terms of the spatial density of deliveries and the mix of weights of the deliveries (e.g., “heavy” items and “light” items), to explore how the strategic design and use of vehicles depends on the nature of demand.
Following analysis with the basic model that includes a single truck and drone, we will explore two other areas. The first is to develop models that allow multiple trucks and drones, and multiple drones per truck to investigate the benefits from additional drone assets. The second is to consider alternative delivery strategies where, for example, the truck would function more as a fixed platform for launching and recovering drones repeatedly, rather than as a delivery vehicle itself. These analyses will consider the important roles played by the characteristics of the drones and the nature of the demand.
- Midwest Transportation Center
- University of Missouri - Saint Louis