A Hybrid Multiobjective Evolutionary Algorithm for Solving Vehicle Routing Problem with Time Windows
Computational Optimization and Applications
A Branch-and-Cut Procedure for the Multimode Resource-Constrained Project-Scheduling Problem
INFORMS Journal on Computing
Dynamic Column Generation for Dynamic Vehicle Routing with Time Windows
Transportation Science
Discrete Applied Mathematics
Formulations and exact algorithms for the vehicle routing problem with time windows
Computers and Operations Research
Computers and Operations Research
Computers and Industrial Engineering
Survey: matheuristics for rich vehicle routing problems
HM'10 Proceedings of the 7th international conference on Hybrid metaheuristics
An improved LNS algorithm for real-time vehicle routing problem with time windows
Computers and Operations Research
Layered formulation for the robust vehicle routing problem with time windows
ISCO'12 Proceedings of the Second international conference on Combinatorial Optimization
Lifted and Local Reachability Cuts for the Vehicle Routing Problem with Time Windows
Computers and Operations Research
A bi-objective vehicle routing problem with time windows: A real case in Tenerife
Applied Soft Computing
Hi-index | 0.00 |
This paper addresses the problem of finding the minimum number of vehicles required to visit a set of nodes subject to time window and capacity constraints. The fleet is homogeneous and is located at a common depot. Each node requires the same type of service. An exact method is introduced based on branch and cut. In the computations, ever increasing lower bounds on the optimal solution are obtained by solving a series of relaxed problems that incorporate newly found valid inequalities. Feasible solutions or upper bounds are obtained with the help of greedy randomized adaptive search procedure (GRASP). A wide variety of cuts is introduced to tighten the linear programming (LP) relaxation of the original mixed-integer program. To find violated cuts, it is necessary to solve a separation problem. A substantial portion of the paper is aimed at describing the heuristics developed for this purpose. A new approach for obtaining feasible solutions from the LP relaxation is also discussed. Numerical results for standard 50- and 100-node benchmark problems are reported.