A tabu search heuristic for the vehicle routing problem
Management Science
Computers and Operations Research
Coding TSP tours as permutations via an insertion heuristic
Proceedings of the 1999 ACM symposium on Applied computing
Experiments on traveling salesman heuristics
SODA '90 Proceedings of the first annual ACM-SIAM symposium on Discrete algorithms
The vehicle routing problem
Reactive GRASP: An Application to a Matrix Decomposition Problem in TDMA Traffic Assignment
INFORMS Journal on Computing
Stochastic Local Search: Foundations & Applications
Stochastic Local Search: Foundations & Applications
Robust Branch-and-Cut-and-Price for the Capacitated Vehicle Routing Problem
Mathematical Programming: Series A and B
Theoretical Aspects of Local Search (Monographs in Theoretical Computer Science. An EATCS Series)
Theoretical Aspects of Local Search (Monographs in Theoretical Computer Science. An EATCS Series)
Dynamic Column Generation for Dynamic Vehicle Routing with Time Windows
Transportation Science
Mathematical Programming: Series A and B
Proceedings of the 11th international symposium on Modeling, analysis and simulation of wireless and mobile systems
The Capacitated m-Ring-Star Problem
Operations Research
Fifty Years of Vehicle Routing
Transportation Science
Min-Max K-vehicles windy rural postman problem
Networks - Route 2007
A Branch-and-Cut algorithm for graph coloring
Discrete Applied Mathematics - Special issue: IV ALIO/EURO workshop on applied combinatorial optimization
Computer Networks: The International Journal of Computer and Telecommunications Networking
New Lower Bounds and Exact Method for the m-PVRP
Transportation Science
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In this work, we investigate a vehicle routing problem where not all clients need to be visited and the goal is to minimize the longest vehicle route. We propose two exact solution approaches for solving the problem: a Branch-and-cut (BC) algorithm and a Local Branching (LB) method that uses BC as its inner solver. Our computational experience indicates that, in practice, the problem is difficult to solve, mainly when the number of vehicles grows. In addition to the exact methods, we present a heuristic that relies on GRASP and on the resolution of a restricted integer program based on a set covering reformulation for the problem. The heuristic was capable of significantly improving the best solutions provided by BC and LB, in one tenth of the times taken by them to achieve their best upper bounds.