Estimating the marginal cost to deliver to individual customers

Wang, Akang; Arbogast, Jeffrey E.; Bonnier, Gildas; Wilson, Zachary; Gounaris, Chrysanthos E.

doi:10.1007/s11081-022-09779-4

Cited by 1 publication

(11 citation statements)

References 39 publications

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“…Smaller instances with 25, 40, and 70 customers were already used by [29,40]. To our knowledge, the best exact approaches in the literature for the MDVRPI are a branch-and-price algorithm by [29] and a BCP algorithm by [40]. The latter algorithm defines the current state-of-the-art for the exact solution of the MDVRPI.…”

Section: Results For the Mdvrpi Instancesmentioning

confidence: 99%

“…Our results are especially good for the largest test instances. For the MDVRPI, our approach is faster for most instances than the algorithm proposed by [40]. In addition, many instances with 100 and 120 customers are solved to optimality for the first time.…”

Section: Discussionmentioning

confidence: 99%

“…Instances with 100 and 120 customers are considered the first time in the literature. Smaller instances with 25, 40, and 70 customers were already used by [29, 40].…”

Section: Computational Experimentsmentioning

confidence: 99%

“…The results for the algorithm by [40] were obtained on an Intel Xeon CPU E5‐2689 v4 server running at 3.10 GHz with 128GB of RAM. We took at the web site https://www.cpubenchmark.net the score of the single thread performance of the processor used by the literature algorithms and used by ours: 1306, 2380, and 2231 points for the algorithms proposed by [29, 40] and us, respectively. The processor speed for the last two algorithms is very similar, and the efficiency of the first algorithm is clearly not on pair with others even considering the difference in processor speed.…”

Section: Computational Experimentsmentioning

confidence: 99%

“…These route variables are generated dynamically by solving the pricing subproblems, usually modeled as RCSPP. Route-based formulations are used for example in [14,21,25,29,40].…”

Section: Literature Reviewmentioning

confidence: 99%

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Solving vehicle routing problems with intermediate stops using VRPSolver models

2022

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In this paper, we propose graph-based models for several vehicle routing problems with intermediate stops: the capacitated multi-trip vehicle routing problem with time windows, the multi-depot vehicle routing problem with inter-depot routes, the arc routing problem with intermediate facilities under capacity and length restrictions and the green vehicle routing problem. In these models, the set of feasible routes is represented by a set of resource constrained paths in one or several graphs. Intermediate stops are supported by the possibility to define negative resource consumption for some arcs. The models that we propose are then solved by VRPSolver, which implements a generic branch-cut-and-price exact algorithm. Thus, a simple parameterization enables us to use several state-of-the-art algorithmic components: automatic stabilization by dual price smoothing, limited-memory rank-1 cuts, reduced cost-based arc elimination, enumeration of elementary routes, and hierarchical strong branching. For each problem, we numerically compare the proposed methodology with the best exact approach found in the literature. State-of-the-art computational results were obtained for all problems except one.

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Section: Results For the Mdvrpi Instancesmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

“…Instances with 100 and 120 customers are considered the first time in the literature. Smaller instances with 25, 40, and 70 customers were already used by [29, 40].…”

Section: Computational Experimentsmentioning

confidence: 99%

Section: Computational Experimentsmentioning

confidence: 99%

“…These route variables are generated dynamically by solving the pricing subproblems, usually modeled as RCSPP. Route-based formulations are used for example in [14,21,25,29,40].…”

Section: Literature Reviewmentioning

confidence: 99%

See 3 more Smart Citations