A Lower Bound for the Split Delivery Vehicle Routing Problem
Operations Research
A new branch-and-cut algorithm for the capacitated vehicle routing problem
Mathematical Programming: Series A and B
Robust Branch-and-Cut-and-Price for the Capacitated Vehicle Routing Problem
Mathematical Programming: Series A and B
A general heuristic for vehicle routing problems
Computers and Operations Research
Mathematical Programming: Series A and B
The Capacitated m-Ring-Star Problem
Operations Research
Subset-Row Inequalities Applied to the Vehicle-Routing Problem with Time Windows
Operations Research
Fifty Years of Vehicle Routing
Transportation Science
A Branch-and-Cut method for the Capacitated Location-Routing Problem
Computers and Operations Research
A multi-start evolutionary local search for the two-echelon location routing problem
HM'10 Proceedings of the 7th international conference on Hybrid metaheuristics
Multi-start heuristics for the two-echelon vehicle routing problem
EvoCOP'11 Proceedings of the 11th European conference on Evolutionary computation in combinatorial optimization
The Two-Echelon Capacitated Vehicle Routing Problem: Models and Math-Based Heuristics
Transportation Science
New Route Relaxation and Pricing Strategies for the Vehicle Routing Problem
Operations Research
An Exact Method for the Capacitated Location-Routing Problem
Operations Research
A column generation approach for the split delivery vehicle routing problem
Operations Research Letters
Improved lower bounds for the Split Delivery Vehicle Routing Problem
Operations Research Letters
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This paper presents an exact method for solving the symmetric two-echelon capacitated vehicle routing problem, a transportation problem concerned with the distribution of goods from a depot to a set of customers through a set of satellite locations. The presented method is based on an edge flow model that is a relaxation and provides a valid lower bound. A specialized branching scheme is employed to obtain feasible solutions. Out of a test set of 93 instances the algorithm is able to solve 47 to optimality, surpassing previous exact algorithms.