Multi-hop driver-parcel matching problem with time windows

Wenyi Chen (Corresponding Author), Martijn Mes, Marco Schutten

Research output: Contribution to journalArticleAcademicpeer-review

63 Citations (Scopus)
134 Downloads (Pure)


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.
Original languageEnglish
Pages (from-to)517-553
Number of pages37
JournalFlexible services and manufacturing journal
Issue number3
Publication statusPublished - Sept 2018


  • UT-Hybrid-D


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