Exact Algorithms for the Clustered Vehicle Routing Problem

Abstract

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A 3-step math heuristic for the static repositioning problem in bike-sharing systems

“…We are not aware of other heuristic approaches that similarly to ours, reduce the network size in such a manner. Battarra et al (2014) studied the clustered vehicle routing problem (CluVRP), where the customers are clustered into predefined clusters, so that a vehicle visiting one customer in the cluster must visit all the remaining customers in the cluster before leaving it. Although this is similar to our heuristic in the fact that a vehicle visits several clusters, there are two main differences between the routing decisions of the CluVRP problem and ours: (i) in the CluVRP problem, the clusters of customers are given as part of the problem's input, while in our problem they are created as part of the solution procedure in order to reduce the complexity of the problem; (ii) in the CluVRP problem, all nodes must be visited, while in our problem it is not a requirement; Other differences between the problems clearly exist, as the operation performed in our repositioning problem is quite more involved than supplying a given quantity to the customers, as in the CluVRP.…”

Hybrid metaheuristics for the Clustered Vehicle Routing Problem

“…This is due to the fact that ILS-Clu performs both intra and inter-cluster LS moves; a balanced instance in terms of number and size of the clusters is a good compromise in terms of CPU time. Finally UHGS was capable of improving the best known solutions for five instances from Battarra et al (2014). The values of these solutions are listed in Table 7.…”

“…The authors adapted two polynomial-sized formulations for the GVRP to the directed CluVRP, but again no computational results were reported. Recently, Battarra et al (2014) proposed exact algorithms for the CluVRP and provided a set of benchmark instances with up to 481 vertices. The best performing algorithm relies on a preprocessing scheme, in which the best Hamiltonian path is precomputed for each pair of endpoints in each cluster.…”

“…Conclusions are drawn in Section 6, and further avenues of research are discussed. Battarra et al (2014) showed that exact algorithms are capable of solving relatively large CluVRP instances. However, the CPU times remain prohibitively long for large-scale or real time applications.…”

Dynamic Vehicle Scheduling for Working Service Network with Dual Demands

“…Vidal et al [7] proposed a unified hybrid genetic search metaheuristic algorithm to solve multiattribute vehicle routing problems. Battarra et al [8] presented new exact algorithms for the clustered vehicle routing problem (CluVRP) and provided two exact algorithms for the problem that is a branch and cut as well as a branch and cut and price.…”