This study focuses on two-echelon synchronized logistics problems in the context of integrated water- and land-based transportation (IWLT) systems. The aim is to meet the increasing demand in city logistics as a result of the growth in transport activities, including parcel delivery, food delivery, and waste collection. We propose two models, a novel mixed integer linear joint model, and a logic-based Benders’ decomposition (LBBD) model, for a two-echelon problem under realistic settings such as multi-trips, time windows, and synchronization at the satellites with no storage and limited resource capacities. The objective is to optimize transfers and satellite assignments, thereby reducing overall logistics costs for street vehicles and vessels. Computational experiments demonstrate that the LBBD model is more robust in terms of solution quality and solution time on average while the added value of the LBBD is more evident when solving large-scale instances with 100 customers, reducing the overall costs by 10.6% on average and significantly reducing the fleet costs on both networks. Furthermore, we assess the effect of changing cost parameters and satellite locations in the proposed IWLT system–analyzing system behavior and suggesting potential improvements–and evaluate several system alternatives in city logistics–consisting of different transportation network designs (single- and two-echelon), vehicle types, and operational constraints. On average, the proposed two-echelon IWLT system reduces the number of kilometers traveled by vehicles at street level by ranging from 20% to 30% compared to a typical single-echelon service design that relies solely on trucks.

A Dynamically Configurable Autonomous Vehicle (DCAV) is a new class of autonomous vehicle concept using a separable design of lower and upper parts—carriers and modules—to allow more flexible operation. A fleet of DCAVs consists of a set of carriers and a set of compatible modules. Different, possibly crowd-sourced, modules can increase the number of use-cases for DCAVs, possibly leading to disruptive changes in the transport sector. This study investigates the use of DCAV system operating on an Autonomous Mobility-on-Demand (AMoD) scenario, combining passenger and freight transport flows. The novel problem is denoted as the Dynamically Configurable Autonomous Vehicle Pickup and Delivery Problem (DCAVPDP). We propose a mixed-integer linear programming (MILP) model aiming to minimize DCAV-fleet size and distance traveled. We compare the performance of a DCAV fleet to the performance of a typical single-purpose fleet (consisting of dedicated passenger and freight vehicles). The numerical study, with 360 instances for each fleet type, considering four people-and-freight demand distribution scenarios, the inclusion of ridesharing, module-and-carrier (de)coupling locations, and different simulation horizon lengths, shows that the proposed modular DCAV system can fulfill a mixed people-and-freight demand using, on average, 18.77% fewer carriers than a regular AMoD system comprised of single-purpose vehicles while increasing on-duty fleet utilization by 4.82%.