We consider a service provider performing pre-planned service for initially known customers with a fleet of vehicles, e.g., parcel delivery. During execution, new dynamic service requests occur, e.g., for parcel pickup. The goal of the service provider is to serve as many dynamic requests as...

We consider an urban instant delivery environment, e.g., meal delivery, in which customers place orders over the course of a day and are promised delivery within a short period of time after an order is placed. Deliveries are made using a fleet of vehicles, each completing one or more trips...

Urban on-demand transportation services are booming, in both passenger transportation and the transportation of goods. The types of service differ in timeliness and compensation and, until now, providers operate larger fleets separately for each type of service. While this may ensure sufficient...

We address the operational management of station-based bike sharing systems (BSSs). In BSSs, users can spontaneously rent and return bikes at any stations in the system. Demand is driven by commuter, shopping, and leisure activities. This demand constitutes a regular pattern of bike usage over...

In recent years, innovative ride-sharing services have gained significant attention. Such services require dynamic decisions on the acceptance of arriving trip requests and vehicle routing to ensure the fulfillment of requests. Decision support for acceptance and routing must be made under...

Operations research requires models that unambiguously define problems and support the generation and presentation of solution methodology. In the field of dynamic routing, capturing the joint evolution of complex sequential routing decisions and stochastic information is challenging, leading to...