Discrete Optimization
Applications of the vehicle routing problem with trailers and transshipments

https://doi.org/10.1016/j.ejor.2012.12.015Get rights and content

Abstract

The vehicle routing problem with trailers and transshipments (VRPTT) is a recent and challenging extension of the well-known vehicle routing problem. The VRPTT constitutes an archetypal representative of the class of vehicle routing problems with multiple synchronization constraints (VRPMSs). In addition to the usual task covering constraints, VRPMSs require further synchronization between vehicles, concerning spatial, temporal, and load aspects. VRPMSs possess considerable practical relevance, but limited coverage in the scientific literature. The purpose of the present paper is to describe how several important types of VRPMSs, such as multi-echelon location-routing problems and simultaneous vehicle and crew routing problems, can be modelled as VRPTTs.

Highlights

► Presents modeling framework for VRPs with multiple synchronization constraints VRPMS. ► Identifies VRP with trailers and transshipments as core VRPMS. ► Represents multi-echelon location-RP and simultaneous vehicle and crew RP as VRPTT. ► Shows versatility of VRPTT as representational framework for many types of rich VRPs. ► Paves way for development of generic solution approaches for VRPMSs.

Introduction

Vehicle routing problems (VRPs) are fundamental planning problems in logistics and transport, and they have been the subject of intensive study for more than half a century now [64], [24], [35]. A recent and challenging extension of the VRP is the vehicle routing problem with trailers and transshipments (VRPTT). The VRPTT constitutes an archetypal representative of the class of vehicle routing problems with multiple synchronization constraints (VRPMSs). VRPMSs are a broad class of VRPs which, despite their considerable practical relevance, have attracted comparatively little attention on the part of science so far. In classical VRPs, synchronization between vehicles is necessary only with respect to which vehicle visits which customer. VRPMSs are VRPs which exhibit additional synchronization requirements with regard to spacial, temporal, and load aspects. A recent survey of synchronization in vehicle routing [21] has shown that practical applications of VRPMSs abound and that the solution of several types of VRPMSs is still a research issue.

The fundamental difference between classical VRPs and VRPMSs is that the latter, contrary to the former, feature the so-called interdependence problem: In standard VRPs, vehicles are independent of one another in that a change in one route does not affect any other route. In VRPMSs, by contrast, a change in one route may have effects on other routes, due to the additional synchronization requirements. In the worst case, a change in one route may render all other routes infeasible. This has considerable implications on potential solution approaches. Actually, most exact and heuristic algorithms for classical VRPs rely on the fact that routes are mutually independent. Consequently, these algorithms cannot directly be applied to solve VRPMSs.

A first step toward solving problems is properly modelling them. Therefore, the contribution of the present paper, similar to the works of Noon and Bean [46], Crainic et al. [15], and Baldacci et al. [2] for other routing problems, is to propose the VRPTT as a unified modelling tool for VRPMSs in general. To this end, it is described how several important types of VRPMSs can be represented as VRPTTs. This demonstrates the versatility of the VRPTT as a representational framework for many types of rich VRPs and points out that the VRPTT needs and deserves further study. The development of exact or heuristic solution algorithms for the VRPTT is beyond the scope of the paper.

The next section describes the VRPTT and develops a graph-theoretic modelling framework which can serve as a basis for algorithmic solution approaches. Subsequent sections describe transformations of classical VRPs and of several types of VRPMSs that were identified as particularly relevant and challenging in the above-mentioned survey. The paper ends with a short conclusion.

Section snippets

Problem description

The VRPTT is a real-world problem arising in raw milk collection at farmyards [19]. Basically, it can be described as follows. There is a set of customers with a given supply. To collect the supply, a set of heterogeneous vehicles stationed at one or several depots is available. In addition to potentially unequal costs, capacity, and temporal availability, the vehicles differ with respect to two orthogonal criteria: First, there are autonomous vehicles able to move in time and space on their

Extensions of the VRP

It is evident that ‘standard’ vehicle routing problems without multiple synchronization constraints, such as the capacitated VRP and the VRP with time windows, are special cases of the VRPTT. By its definition, the VRPTT already encompasses the heterogeneous fleet versions of these problems. Real-world constraints such as multiple capacity constraints, vehicle-specific time windows etc. are also easily accommodated.

Moreover, the concepts of subnetworks and compatibilities between vehicles with

N-echelon vehicle and location-routing problems

Gonzalez Feliu et al. [27] and Perboli et al. [50] formally introduce the class of multi-echelon (or N-echelon) vehicle routing problems and are the first to use these terms (see also [32], [51], [29]). The basic idea behind this problem class is that customers are not delivered directly from a central depot, but via N legs in an N-stage distribution network. An N-stage distribution network contains N + 1 levels of location. Echelon n  {1,  , N} considers transports from location level n  1 to n, see

Simultaneous vehicle and crew routing and scheduling problems

For the most part, the VRP literature does not distinguish between a vehicle and its driver. In their monograph on VRPs, for example, Toth and Vigo [64] state that throughout, ‘the constraints imposed on drivers are imbedded in those associated with the corresponding vehicles’. However, it is a fact that drivers regularly need breaks and rests and must obey the existing pertinent social legislation and trade union rules regarding driving, break, and rest times. On the other hand, vehicles can

Personnel dispatching problems with spatio-temporal synchronization constraints

There is quite a number of applications where persons must be synchronized with respect to space and time to perform some kind of service, but where no load transfers are performed and no vehicle capacities are relevant. Examples include the dispatching of service technicians with different qualifications who have to meet to repair machines, or homecare staff routing, where two nurses must visit a disabled person at the same time for lifting purposes or with a specified delay to apply medicine

Problems with more than two types of vehicle

After the preceding explanations, it is easy to imagine the situation where more than two types of vehicle may be allowed or required to join to move in space. To be precise, two aspects must be distinguished: It is possible that (i) an autonomous elementary or composite object can ‘pull’ more than one elementary non-autonomous object and that (ii) two or more non-autonomous objects must join to form an autonomous object. These extensions are of practical as well as theoretical relevance.

A

Pickup-and-delivery problems with (trailers and) transshipments

A popular extension of the classical VRP is the class of vehicle routing problems with pickups and deliveries, or pickup-and-delivery problems (PDPs). In a classical VRP, either each customer has a certain supply to be collected and brought to a depot, or each customer has a certain demand to be fulfilled from a depot. In PDPs, there is a set of transport requests that must be fulfilled. A request consists in the transport of a certain amount of load from a request-specific pickup location to a

Conclusion

Vehicle routing problems with multiple synchronization constraints are challenging optimization problems. In contrast to many other types of VRPs and despite their practical relevance, VRPMSs have only recently entered the focus of the scientific community. This may partly be owed to the fact that they are difficult to solve, and that solution approaches for classical VRPs cannot directly be applied to VRPMSs. This author is unaware of any solution procedure for N-echelon vehicle or

Acknowledgement

This research was funded by the Deutsche Forschungsgemeinschaft (DFG) under Grant No. IR 122/5-1.

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