A Branch-and-Price Algorithm for the Vehicle Routing Problem with 2-Dimensional Loading Constraints

2016 ◽  
pp. 321-336
Author(s):  
Telmo Pinto ◽  
Cláudio Alves ◽  
José Valério de Carvalho
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Branch And Price ◽  
Routing Problem ◽  
Loading Constraints ◽  
Price Algorithm

A Branch-and-price algorithm for a Vehicle Routing Problem with Cross-Docking

2011 ◽  
Vol 37 ◽  
pp. 249-254 ◽  
Author(s):  
Fernando Afonso Santos ◽  
Geraldo Robson Mateus ◽  
Alexandre Salles da Cunha
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Branch And Price ◽  
Routing Problem ◽  
Cross Docking ◽  
Price Algorithm

A branch‐and‐price algorithm for the vehicle routing problem with time windows on a road network

Networks ◽  
2018 ◽  
Vol 73 (4) ◽  
pp. 401-417 ◽  
Author(s):  
Hamza Ben Ticha ◽  
Nabil Absi ◽  
Dominique Feillet ◽  
Alain Quilliot ◽  
Tom Van Woensel
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Road Network ◽  
Time Windows ◽  
Branch And Price ◽  
Routing Problem ◽  
Price Algorithm

A branch-and-price algorithm for the Vehicle Routing Problem with Deliveries, Selective Pickups and Time Windows

2010 ◽  
Vol 206 (2) ◽  
pp. 341-349 ◽  
Author(s):  
Gabriel Gutiérrez-Jarpa ◽  
Guy Desaulniers ◽  
Gilbert Laporte ◽  
Vladimir Marianov
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Time Windows ◽  
Branch And Price ◽  
Routing Problem ◽  
Price Algorithm

Learning-Based Branch-and-Price Algorithms for the Vehicle Routing Problem with Time Windows and Two-Dimensional Loading Constraints

2021 ◽  
Author(s):  
Xiangyi Zhang ◽  
Lu Chen ◽  
Michel Gendreau ◽  
André Langevin
Keyword(s):  
Vehicle Routing ◽  
Operations Research ◽  
Vehicle Routing Problem ◽  
Time Windows ◽  
Learning Model ◽  
Exact Algorithms ◽  
Two Dimensional ◽  
Branch And Price ◽  
Routing Problem ◽  
Loading Constraints

A capacitated vehicle routing problem with two-dimensional loading constraints is addressed. Associated with each customer are a set of rectangular items, the total weight of the items, and a time window. Designing exact algorithms for the problem is very challenging because the problem is a combination of two NP-hard problems. An exact branch-and-price algorithm and an approximate counterpart are proposed to solve the problem. We introduce an exact dominance rule and an approximate dominance rule. To cope with the difficulty brought by the loading constraints, a new column generation mechanism boosted by a supervised learning model is proposed. Extensive experiments demonstrate the superiority of integrating the learning model in terms of CPU time and calls of the feasibility checker. Moreover, the branch-and-price algorithms are able to significantly improve the solutions of the existing instances from literature and solve instances with up to 50 customers and 103 items. Summary of Contribution: We wish to submit an original research article entitled “Learning-based branch-and-price algorithms for a vehicle routing problem with time windows and two-dimensional loading constraints” for consideration by IJOC. We confirm that this work is original and has not been published elsewhere, nor is it currently under for publication elsewhere. In this paper, we report a study in which we develop two branch-and-price algorithms with a machine learning model injected to solve a vehicle routing problem integrated the two-dimensional packing. Due to the complexity brought by the integration, studies on exact algorithms in this field are very limited. Our study is important to the field, because we develop an effective method to significantly mitigate computational burden brought by the packing problem so that exactness turns to be achievable within reasonable time budget. The approach can be generalized to the three-dimensional case by simply replacing the packing algorithm. It can also be adapted for other VRPs when high-dimensional loading constraints are concerned. Broadly speaking, the study is a typical example of adopting supervised learning to achieve acceleration for operations research algorithms, which expands the envelop of computing and operations research. Hence, we believe this manuscript is appropriate for publication by IJOC.

A Branch-and-Price Algorithm for the Multidepot Vehicle Routing Problem with Interdepot Routes

2014 ◽  
Vol 48 (3) ◽  
pp. 425-441 ◽  
Author(s):  
Ibrahim Muter ◽  
Jean-François Cordeau ◽  
Gilbert Laporte
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Branch And Price ◽  
Routing Problem ◽  
Price Algorithm

A Branch-and-Price Algorithm for the Vehicle Routing Problem with Stochastic Demands and Probabilistic Duration Constraints

2020 ◽  
Author(s):  
Alexandre M. Florio ◽  
Richard F. Hartl ◽  
Stefan Minner ◽  
Juan-José Salazar-González
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Negative Binomial ◽  
Probability Distributions ◽  
Sensitivity Analyses ◽  
Branch And Price ◽  
Expected Cost ◽  
Routing Problem ◽  
Stochastic Demands ◽  
Price Algorithm

In many routing applications, it is necessary to place limits on the duration of the individual routes. When demands are stochastic and restocking during route execution is allowed, the durations of the resulting routes are also stochastic. In this paper, we consider the vehicle routing problem with stochastic demands and probabilistic duration constraints (VRPSD-PDC). We assume optimal restocking, which means that, during the route execution, replenishment trips to the depot are performed in an optimal way. The resulting optimization problem calls for a set of routes with minimal total expected cost for visiting all customers, such that the duration of each route, with a given probability, does not exceed a prescribed limit. We solve the VRPSD-PDC with a novel branch-and-price algorithm. An orienteering-based completion bound is proposed to control the growth of labels in the pricing algorithm. Feasibility of a priori routes is verified by applying Chebyshev’s bounds, by Monte Carlo simulation and statistical inference, or by analytically deriving the distribution of the route duration. Consistency checks are incorporated into the branch-and-price framework to detect statistical errors. Computational experiments are performed with demands following binomial, Poisson, or negative binomial probability distributions and with duration constraints enforced at the levels of 90%, 95%, and 98%. Optimal solutions to the VRPSD-PDC may contain routes that serve an expected demand that is larger than the capacity of the vehicle. These solutions actively employ optimal restocking to reduce traveling costs and the number of required vehicles. Sensitivity analyses indicate that high demand variability negatively impacts the solution, both in terms of total expected cost and the number of routes employed.

scholarly journals A branch-and-price algorithm for the vehicle routing problem with roaming delivery locations

2017 ◽  
Vol 100 ◽  
pp. 115-137 ◽  
Author(s):  
Gizem Ozbaygin ◽  
Oya Ekin Karasan ◽  
Martin Savelsbergh ◽  
Hande Yaman
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Branch And Price ◽  
Routing Problem ◽  
Price Algorithm
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