Joint Vehicle and Crew Routing and Scheduling

Edward Lam (), Pascal Van Hentenryck () and Phil Kilby ()
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Edward Lam: Monash University, Caulfield East, Victoria 3145, Australia; CSIRO Data61, Canberra, Australian Capital Territory 2601, Australia
Pascal Van Hentenryck: Georgia Institute of Technology, Atlanta, Georgia 30332
Phil Kilby: CSIRO Data61, Canberra, Australian Capital Territory 2601, Australia

Transportation Science, 2020, vol. 54, issue 2, 488-511

Abstract: Traditional vehicle routing problems implicitly assume that only one crew operates a vehicle for the entirety of its journey. However, this assumption is violated in many applications arising in humanitarian and military logistics. This paper considers a joint vehicle and crew routing and scheduling problem in which crews are able to interchange vehicles, resulting in space and time interdependencies between vehicle routes and crew routes. The problem is formulated as a mixed integer programming (MIP) model and a constraint programming (CP) model that overlay crew routing constraints over a standard vehicle routing problem. The constraint program uses a novel optimization constraint to detect infeasibility and to bound crew objectives. This paper also explores methods using large neighborhood search over the MIP and CP models. Experimental results indicate that modeling the vehicle and crew routing problems jointly and supporting vehicle interchanges for crews may bring significant benefits in cost reduction compared with a method that sequentializes these decisions.

Keywords: vehicle routing; vehicle scheduling; crew routing; crew scheduling; synchronization; mixed integer programmin; constraint programming; hybrid optimization; large neighborhood search (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ortrsc:v:54:y:2020:i:2:p:488-511

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