Branch and Cut and Price for the Pickup and Delivery Problem with Time Windows
Transportation Science
The SR-GCWS hybrid algorithm for solving the capacitated vehicle routing problem
Applied Soft Computing
Fifty Years of Vehicle Routing
Transportation Science
Heuristic and exact algorithms for a min-max selective vehicle routing problem
Computers and Operations Research
Survey: matheuristics for rich vehicle routing problems
HM'10 Proceedings of the 7th international conference on Hybrid metaheuristics
An Exact Algorithm for the Period Routing Problem
Operations Research
An Exact Algorithm for the Pickup and Delivery Problem with Time Windows
Operations Research
Proceedings of the 2010 Summer Computer Simulation Conference
New Route Relaxation and Pricing Strategies for the Vehicle Routing Problem
Operations Research
Computers and Operations Research
Efficient local search on the GPU-Investigations on the vehicle routing problem
Journal of Parallel and Distributed Computing
The Pickup and Delivery Problem with Cross-Docking
Computers and Operations Research
A Branch-and-Cut Algorithm for the Symmetric Two-Echelon Capacitated Vehicle Routing Problem
Transportation Science
New Lower Bounds and Exact Method for the m-PVRP
Transportation Science
A hybrid approach for the vehicle routing problem with three-dimensional loading constraints
Computers and Operations Research
An Exact Algorithm for the Multitrip Vehicle Routing Problem
INFORMS Journal on Computing
Bi-Objective Bus Routing: An Application to School Buses in Rural Areas
Transportation Science
Survey of Green Vehicle Routing Problem: Past and future trends
Expert Systems with Applications: An International Journal
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This paper presents a new exact algorithm for the Capacitated Vehicle Routing Problem (CVRP) based on the set partitioning formulation with additional cuts that correspond to capacity and clique inequalities. The exact algorithm uses a bounding procedure that finds a near optimal dual solution of the LP-relaxation of the resulting mathematical formulation by combining three dual ascent heuristics. The first dual heuristic is based on the q-route relaxation of the set partitioning formulation of the CVRP. The second one combines Lagrangean relaxation, pricing and cut generation. The third attempts to close the duality gap left by the first two procedures using a classical pricing and cut generation technique. The final dual solution is used to generate a reduced problem containing only the routes whose reduced costs are smaller than the gap between an upper bound and the lower bound achieved. The resulting problem is solved by an integer programming solver. Computational results over the main instances from the literature show the effectiveness of the proposed algorithm.