A Novel Mathematical Model for Cross Dock Open-Close Vehicle Routing Problem with Splitting

Alinaghian, Mahdi; Kalantari, Mina Rezaei; Bozorgi-Amiri, Ali; Raad, Nima Golghamat

doi:10.5815/ijmsc.2016.03.02

Cited by 4 publications

(2 citation statements)

References 22 publications

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“…Salari et al (2010) proposed a heuristic improvement procedure for the OVRP based on integer linear programming techniques to improve a feasible solution of a combinatorial optimization problem. Alinaghian et al (2016) proposed a mathematical model in which open paths are used into the problem of cross-docks. To model the open path, a dummy node is defined, whose distance to other nodes is considered zero, and from which the route starts.…”

Section: Literature Reviewmentioning

confidence: 99%

The electric vehicle routing problem with backhauls

Echeverri¹,

Cubides²,

Bustamante³

2020

10.5267/j.ijiec

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In the classical vehicle routing problem with backhauls (VRPB) the customers are divided into two sets; the linehaul and backhaul customers, so that the distribution and collection services of goods are separated into different routes. This is justified by the need to avoid the reorganization of the loads inside the vehicles, to reduce the return of the vehicles with empty load and to give greater priority to the customers of the linehaul. Many logistics companies have special responsibility to make their operations greener, and electric vehicles (EVs) can be an efficient solution. Thus, when the fleet consists of electric vehicles (EVs), the driving range is limited due to their battery capacities and, therefore, it is necessary to visit recharging stations along their route. In this paper the electric vehicle routing problem with backhauls (EVRPB) is introduced and formulated as a mixed integer linear programming model. This formulation is based on the generalization of the open vehicle routing problem considering a set of new constraints focussed on maintaining the arborescence condition of the linehaul and backhaul paths. Different charging points for the EVs are considered in order to recharge the battery at the end of the linehaul route or during the course of the backhaul route. Finally, a heuristic initialization methodology is proposed, in which an auxiliary graph is used for the efficient coding of feasible solutions to the problem. The operation and effectiveness of the proposed formulation is tested on two VRPB instance datasets of literature which have been adapted to the EVRPB.

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Section: Literature Reviewmentioning

confidence: 99%

The electric vehicle routing problem with backhauls

Echeverri¹,

Cubides²,

Bustamante³

2020

10.5267/j.ijiec

View full text Add to dashboard Cite

show abstract

“…Salari et al proposed a heuristic improvement procedure for the OVRP based on integer LP techniques to improve a feasible solution of a combinatorial optimization problem. Alinaghian et al proposed a mathematical model in which open paths are used into the problem of cross‐docks. To model the open path, a dummy node is defined, whose distance to other nodes is considered zero, and from which the route starts.…”

Section: Literature Reviewmentioning

confidence: 99%

An MIP formulation for the open location‐routing problem considering the topological characteristic of the solution‐paths

2019

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In the open location‐routing problem (OLRP), one has a set of candidate depots to be installed and the vehicles start from the depot, visit all customers, and are not required to return to the depot after completing their service. Thus, the OLRP involves the problems of facility location and open vehicle routing. In this paper, a new mixed integer programming formulation for the OLRP is presented by proposing a set of constraints to obtain valid solutions formed by a graph consisting of a spanning tree in each connected component of the graph. This approach results in an alternative way of avoiding generating subtours, which significantly simplifies the set of constraints associated with the connectivity of the solution and the vehicle capacity requirements. The computational results show that the proposed formulation is competitive against state of‐the‐art methods for this type of problems.

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