A three-phase matheuristic for capacitated multi-commodity fixed-cost network design with design-balance constraints

Vu, Duc Minh; Crainic, Teodor Gabriel; Toulouse, Michel

doi:10.1007/s10732-013-9225-y

Cited by 32 publications

(22 citation statements)

References 18 publications

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“…Pedersen et al (2009) also proposed a two-phase tabu search method for the arc-based formulation. Meta-heuristic algorithms improving over the results of Pedersen et al (2009) were proposed by Chouman and Crainic (2010) and Vu et al (2012), the latter being used as a subroutine in the approach presented in this paper. This requirement has been modeled for various modes of transportation, e.g., Barnhart and Schneur (1996); for air-based express package delivery, Lai and Lo (2004) for ferries, Andersen and Christiansen (2009);Andersen et al (2009a) for intermodal rail, and Erera et al (2012); Smilowitz et al (2003) for trucking.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Lastly, we note that we formulate and solve both of these optimization problems as a minimum cost, maximum flow problem (Ahuja et al, 1994). See Vu et al (2012) for details of how a similar procedure was done for a network design problem with Euleriantype constraints.…”

Section: Creating a Feasible Solution To Sndrc From A Solution To Ap(mentioning

confidence: 99%

“…Then, a subgraph of G is created based on the arcs that appear in those cycles. Because some cycles may share arcs, this graph may not be Eulerian and thus we next add arcs to the subgraph to make it Eulerian with the procedure presented in Vu et al (2012). Finally, a depth-first search-type approach is performed on this subgraph to extract cycles which are T M AX periods long.…”

Section: Intensification and Diversificationmentioning

confidence: 99%

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Service Network Design with Resource Constraints

Crainic

Hewitt

Toulouse

et al. 2016

Transportation Science

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We first present a new service network design model for freight consolidation carriers, one that both routes commodities and the resources needed to transport them while explicitly recognizing that there are limits on how many resources are available at each terminal. We next present a solution approach that combines column generation, meta-heuristic, and exact optimization techniques to produce high-quality solutions. We demonstrate the efficacy of the approach with an extensive computational study and benchmark its performance against a leading commercial solver.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Creating a Feasible Solution To Sndrc From A Solution To Ap(mentioning

confidence: 99%

Section: Intensification and Diversificationmentioning

confidence: 99%

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Service Network Design with Resource Constraints

Crainic

Hewitt

Toulouse

et al. 2016

Transportation Science

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“…Constraint (3) is the flow balance constraint, making sure that all commodities are shipped from their origins to destinations. Constraint (4) is the design balance constraint (Pederson et al, 2008;Vu et al, 2013), which ensures all vehicles finally return to their origins to get ready for next service period. Constraints (5) and (6) are used to guarantee the nonnegativity of decision variables and the integrity of design variables.…”

Section: Node-arc Modelmentioning

confidence: 99%

“…Due to various restrictions, routes must often take the form of cycles so that drivers can come back home after a certain period of time. Although the vehicle balancing constraint ensures that the number of departing vehicles equals the number of incoming vehicles (Vu et al, 2013), the Node-Arc service network design model does not directly determine routes for vehicles. This is very different from the classic vehicle routing problem (VRP).…”

Section: Introductionmentioning

confidence: 99%

A scheme for determining vehicle routes based on Arc-based service network design

Jiang

Bai

Atkin

et al. 2016

INFOR: Information Systems and Operational Research

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A note on versions:The version presented here may differ from the published version or from the version of record. If you wish to cite this item you are advised to consult the publisher's version. Please see the repository url above for details on accessing the published version and note that access may require a subscription. Abstract-In freight transportation, less-than-truckload carriers often need to assign each vehicle a cyclic route so that drivers can come back home after a certain period of time. However, the NodeArc model for service network design addresses decisions on each arc and does not determine routes directly, although the vehicle balancing constraint ensures that the number of outgoing vehicles equals the number of incoming vehicles at each node. How to transform the optimized service network into a set of vehicle routes remains an important problem that has not yet been studied. In this paper, we propose a three-phase scheme to address this problem. In the first stage, we present an algorithm based on the depth-first search to find all of the different cyclic routes in a service network design solution. In the second stage, we propose to prune poor cyclic routes using real-life constraints so that a collection of acceptable vehicle routes can be obtained before route assignment. Some of the pruning can also be done in the first stage to speed up the proposed algorithm. In the third stage, we formulate the problem of selecting a set of cyclic routes to cover the entire network as a weighted set covering problem. The resulting model is formulated as an integer program and solved with IBM ILOG CPLEX solver. Experimental results on benchmark instances for service network design indicate the effectiveness of the proposed scheme which gives high-quality solutions in an efficient way.

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Service Network Design

Crainic

Hewitt

2020

Network Design With Applications to Transportation and Logistics

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A three-phase matheuristic for capacitated multi-commodity fixed-cost network design with design-balance constraints

Cited by 32 publications

References 18 publications

Service Network Design with Resource Constraints

Service Network Design with Resource Constraints

A scheme for determining vehicle routes based on Arc-based service network design

Service Network Design

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