Crowdsourced shipping can result in significant economic and social benefits. For a shipping company, it has a potential cost advantage and creates opportunities for faster deliveries. For the society, it can provide desirable results by reducing congestion and air pollution. Despite the great potential, crowdsourced shipping is not well studied. With the aim of using the spare capacities along the existing transportation flows of the crowd to deliver small-to-medium freight volumes, this paper defines the multi-driver multi-parcel matching problem and proposes a general ILP formulation, which incorporates drivers' maximum detour, capacity limits, and the option of transferring parcels between drivers. Due to the high computational complexity, we develop two heuristics to solve the problem. The numerical study shows that crowdsourced shipping can be an economic viable and sustainable option, depending on the spatial characteristics of the network and drivers' schedules. Furthermore, the added benefits increase with an increasing number of participating drivers and parcels.

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Ride-sharing has been widely acknowledged as an effective solution for reducing travel costs, congestion and pollution. This paper considers the ride-sharing problem of the scheduled commuter and business traffic within a closed community of companies that agree to share the calendars of their employees. We propose a general ILP formulation for the aforementioned ride-sharing problem, which incorporates return restrictions in order to satisfy the business needs, as well as meeting points and the option for riders to transfer between drivers. All the instances with 40 and 60 participants, and most of the instances with 80 participants can be solved to optimality within a time limit of 2 hours. Using instances of up to 100 participants, the ILP can be solved with a gap of no more than 1.5% within the time limit. Due to the high computational complexity, we develop a constructive heuristic that is based on the saving concepts. This heuristic is also able to combine ride-sharing with the use of an external mobility service provider. Our numerical study shows that ridesharing can be an effective way of reducing the number of trips and vehicle-miles. Particularly, ride-sharing creates more benefits when the participation is high, and when the origins and the destinations of the trips are more spatially concentrated. The results show that ride-sharing can create up to 35.2% mileage savings and up to 23.3% reduction in the number of cars needed to fulfill employees' travel schedules. We also illustrate our model using a real-life ride-sharing problem of a Dutch consultancy and research firm.