Optimization of a Physical Internet-based Mixed Crowd-shipping, Ride-sharing, and On-Demand Transit Scheme

Climate change, together with the growth of urban populations and e-commerce, highlights the need for innovative and sustainable mobility solutions that provide attractive services for both people and goods. In this respect, we propose an optimization model for a mixed people/goods transport network that integrates the concepts of Physical Internet (PI), ride-sharing, on-demand micro-transit, and crowd-shipping into a single framework. In this unified framework, private drivers offer transport capacity and agree to carry passengers and/or goods along their routes. In addition, in case there were no available private drivers, an on-demand service can be activated, especially in case of urgent deliveries or absence of alternatives for riders. Following the PI concept, goods can be disassembled, transported using different vehicles, and reassembled at their destination. This approach allows better utilization of the available transport capacity, increases the flexibility of allocations between goods and drivers, and reduces the need for additional vehicles. A centralized transport supply manager collects all travel requests and offers, determines the best allocation between drivers and people/goods, and optimizes driver routes and schedules. The proposed model is applied to a simple case study to test its effectiveness. Results show that the model effectively allocates people and goods to drivers while ensuring that all pick-up and delivery time windows are met, the number of allocated people and goods is maximized, and driver travel times are minimized. This model contributes to the development of innovative urban transport schemes that can serve as an alternative or complement to traditional public transport and logistic systems. By increasing urban mobility efficiency, it aims to reduce car dependency, pollution, and traffic congestion while simultaneously increasing vehicle occupancy rates.