Simultaneous Vehicle and Crew Routing and Scheduling for Partial- and Full-Load Long-Distance Road Transport

Drexl, Michael; Rieck, Julia; Sigl, Thomas; Press, Bettina

doi:10.1007/bf03342751

Cited by 20 publications

(19 citation statements)

References 25 publications

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“…All of these approaches assume that a single driver is assigned to each vehicle throughout the planning horizon. Drexl et al (2013) propose a heuristic algorithm for a variant of the problem where the driver to vehicle assignment can be changed dynamically.…”

Section: Related Workmentioning

confidence: 99%

To team up or not: single versus team driving in European road freight transport

2020

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The last decades have seen a tremendous amount of research being devoted to effectively managing vehicle fleets and minimizing empty mileage. However, in contrast to, e.g., the air transport sector, the question of how to best assign crews to vehicles, has received very little attention in the road transport sector. The vast majority of road freight transport in Europe is conducted by single drivers and team driving is often only conducted if there are special circumstances, e.g., security concerns. While it is clear that transport companies want to avoid the costs related to additional drivers, vehicles manned by a single driver sit unused whenever the driver takes a mandatory break or rest. Team drivers, on the other hand, can travel a much greater distance in the same amount of time, because mandatory breaks and rests are required less frequently. This paper investigates under which conditions trucking companies should use single or team driving to maximize their profitability. We present a novel optimization approach for simultaneously optimizing routes and crewing decisions and provide experimental evidence that, for a wide range of cost factors, operating a fleet with a mix of team and single drivers can significantly reduce operational costs when compared to typical profit margins in the sector.

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Section: Related Workmentioning

confidence: 99%

To team up or not: single versus team driving in European road freight transport

2020

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“…Works that study problems where different types of autonomous and nonautonomous objects that may join and separate en route (and not only at a central depot) are used to fulfil tasks are Bürckert et al , Hollis et al , Cheung et al , Kim et al , and Drexl et al . All of these papers develop heuristic solution approaches: Bürckert et al consider a dynamic pickup‐and‐delivery problem using lorries, trailers, and swap‐body platforms in the context of long‐haul transport and solve their problem with a holonic multiagent system.…”

Section: Literature Reviewmentioning

confidence: 99%

“…All of these papers develop heuristic solution approaches: Bürckert et al consider a dynamic pickup‐and‐delivery problem using lorries, trailers, and swap‐body platforms in the context of long‐haul transport and solve their problem with a holonic multiagent system. Both Hollis et al and Drexl et al solve a simultaneous vehicle and driver routing problem (with application in postal logistics in Australia and long‐haul road transport in Europe, respectively) with two‐stage algorithms. Hollis et al first compute abstract vehicle routes by solving a rich pickup‐and‐delivery problem by heuristic column generation.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Then, concrete vehicles and drivers are assigned by taking an integrated vehicle and crew scheduling approach, again done by solving an MIP by heuristic column generation. Drexl et al determine routes for concrete vehicles in the first stage, and then compute routes for drivers, based on the vehicle routes from the first stage. They use the same large neighborhood search algorithm in both stages.…”

Section: Literature Reviewmentioning

confidence: 99%

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Branch‐and‐cut algorithms for the vehicle routing problem with trailers and transshipments

Drexl

2013

Networks

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This article studies the vehicle routing problem with trailers and transshipments (VRPTT), a practically relevant, but challenging, generalization of the classical vehicle routing problem. The article makes three contributions: (i) Building on a nontrivial network representation, two mixed-integer programming formulations for the VRPTT are proposed. (ii) Based on these formulations, five different branch-and-cut algorithms are developed and implemented. (iii) The computational behavior of the algorithms is analyzed in an extensive computational study, using a large number of test instances designed to resemble real-world VRPTTs

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“…Given the jobs to be serviced and the roster of workers for each shift, the problem is to form teams and assign them to the jobs, to service as many flights as possible. Drexl et al (2011) studies a simultaneous vehicle and crew routing and scheduling problem arising in long-distance road transport. In their study, they abandon the assumption of fixed assignment of drivers to vehicles and allow for vehicle/deriver changes at some relay stations.…”

Section: Introduction and Literature Reviewmentioning

confidence: 99%

Scheduling multi-skilled manpower with considering teams replacement and site-dependent vehicles routing

Kiani

Seidgar

Mahdavi

2017

IJMOR

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Abstract:In this paper, a combined manpower-vehicle routing problem (CMVRP) is presented that a central depot is considered in which a set of vehicles and a set of multi-skilled teams originate from it to move toward each customer's site for servicing tasks. This problem deals with scheduling of multi-skilled manpower to service a set of tasks with due dates and at the same, routing of the vehicles which are used for moving this manpower. Teams are in different range of competency that it will affect the service time duration. Vehicles are in different moving speeds and costs and not all the vehicles are capable to move toward all the customers' sites. The objective is to find an efficient schedule for the teams and vehicles movement in order to minimise the total cost of servicing, routing and lateness penalties. In this paper, a mixed integer programming model is presented and two meta-heuristics approaches of genetic algorithm (GA) and particle swarm optimisation (PSO) are developed to solve the generated problems. Furthermore, Taguchi experimental design method is applied to set the proper values of parameters. The available results show the higher performance of proposed GA compared with PSO, in quality of solutions within comparatively shorter periods of time.Keywords: vehicle routing problem; VRP; manpower; competency of working team; genetic algorithm; particle swarm optimisation; PSO.Reference to this paper should be made as follows: Kiani, M., Seidgar, H. and Mahdavi, I. (2017) 'Scheduling multi-skilled manpower with considering teams replacement and site-dependent vehicles routing', Int.

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Simultaneous Vehicle and Crew Routing and Scheduling for Partial- and Full-Load Long-Distance Road Transport

Cited by 20 publications

References 25 publications

To team up or not: single versus team driving in European road freight transport

To team up or not: single versus team driving in European road freight transport

Branch‐and‐cut algorithms for the vehicle routing problem with trailers and transshipments

Scheduling multi-skilled manpower with considering teams replacement and site-dependent vehicles routing

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