Abstract:This paper introduces the vehicle routing problem with partial outsourcing (VRPPO) in which a customer can be served by a single private vehicle, by a common carrier, or by both a single private vehicle and a common carrier. As such, it is a variant of the vehicle routing problem with private fleet and common carrier (VRPPC). The objective of the VRPPO is to minimize fixed and variable costs of the private fleet plus the outsourcing cost. We propose two different path-based formulations for the VRPPO and solve… Show more
“…Table 5 compares our results to the exact results obtained by Baller et al (2020) on the VRPPC. Each line aggregates the results for one category of instances.…”
Section: Results On Hff-vrp-tw-pc Benchmark Instancesmentioning
confidence: 96%
“…We benchmarked the results of the LNS-SPP algorithm against the most recent works on the HFF-VRP-TW-PC. Baller et al (2020) derive instances from those of Dabia et al (2019) and propose two categories of instances with high and low outsourcing costs, respectively. As in the original instances, they were adapted from Solomon's instances (Solomon, 1987).…”
Section: Results On Hff-vrp-tw-pc Benchmark Instancesmentioning
confidence: 99%
“…Each category of instances is made up of 56 instances. The column entitled # shows the number of instances (out of 56) solved to optimality by the BCP algorithm of Baller et al (2020) within the one hour time limit. Note that these results ignore instances for which the optimal solution consists in shipping all orders in LTL.…”
Section: Results On Hff-vrp-tw-pc Benchmark Instancesmentioning
confidence: 99%
“…Both models are solved with a Branch-and-Cut-and-Price algorithm, which is evaluated on instances of Liu and Shen (1999), that were adapted to handle the case of subcontracting costs and a fleet limited to three units of each vehicle type. Baller et al (2020) study the VRP with Partial Outsourcing (VRPPO), in which delivery to any customer can be split between the private fleet and external carriers. Two route-based SPP formulations are proposed as well as a Branch-and-Cut-and-Price to solve them.…”
Section: Exact Methodsmentioning
confidence: 99%
“…Comparison to optimal solutions: results of LNS-SPP on VRP-PC instances compared to the branch-and-cutand-price ofBaller et al (2020) …”
“…Table 5 compares our results to the exact results obtained by Baller et al (2020) on the VRPPC. Each line aggregates the results for one category of instances.…”
Section: Results On Hff-vrp-tw-pc Benchmark Instancesmentioning
confidence: 96%
“…We benchmarked the results of the LNS-SPP algorithm against the most recent works on the HFF-VRP-TW-PC. Baller et al (2020) derive instances from those of Dabia et al (2019) and propose two categories of instances with high and low outsourcing costs, respectively. As in the original instances, they were adapted from Solomon's instances (Solomon, 1987).…”
Section: Results On Hff-vrp-tw-pc Benchmark Instancesmentioning
confidence: 99%
“…Each category of instances is made up of 56 instances. The column entitled # shows the number of instances (out of 56) solved to optimality by the BCP algorithm of Baller et al (2020) within the one hour time limit. Note that these results ignore instances for which the optimal solution consists in shipping all orders in LTL.…”
Section: Results On Hff-vrp-tw-pc Benchmark Instancesmentioning
confidence: 99%
“…Both models are solved with a Branch-and-Cut-and-Price algorithm, which is evaluated on instances of Liu and Shen (1999), that were adapted to handle the case of subcontracting costs and a fleet limited to three units of each vehicle type. Baller et al (2020) study the VRP with Partial Outsourcing (VRPPO), in which delivery to any customer can be split between the private fleet and external carriers. Two route-based SPP formulations are proposed as well as a Branch-and-Cut-and-Price to solve them.…”
Section: Exact Methodsmentioning
confidence: 99%
“…Comparison to optimal solutions: results of LNS-SPP on VRP-PC instances compared to the branch-and-cutand-price ofBaller et al (2020) …”
For many variants of vehicle routing and scheduling problems solved by a branch-price-and-cut (BPC) algorithm, the pricing subproblem is an elementary shortest-path problem with resource constraints (SPPRC) typically solved by a dynamic-programming labeling algorithm. Solving the SPPRC subproblems consumes most of the total BPC computation time. Critical to the performance of the labeling algorithms and thus the BPC algorithm as a whole is the use of effective dominance rules. Classical dominance rules rely on a pairwise comparison of labels and have been used in many labeling algorithms. In contrast, partial dominance describes situations where several labels together are needed to dominate another label, which can then be safely discarded. In this work, we consider SPPRCs, where a linear tradeoff describes the relationship between two resources. We derive a unified partial dominance rule to be used in ad hoc labeling algorithms for solving such SPPRCs as well as insights into its practical implementation. We introduce partial dominance for two important variants of the vehicle routing problem, namely the electric vehicle routing problem with time windows with a partial recharge policy and the split-delivery vehicle routing problem with time windows (SDVRPTW). Computational experiments show the effectiveness of the approach, in particular for the SDVRPTW, leading to an average reduction of 20% of the total BPC computation time, with savings of 30% for the more difficult instances requiring more than 600 s of computation time.
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