The Vehicle Routing Problem (VRP) is one of the most challenging combinatorial optimization task. Defined more than 40 years ago, this problem consists in designing the optimal set of routes for fleet of vehicles in order to serve a given set of customers. The interest in VRP is motivated by its practical relevance as well as by its considerable difficulty. This web is dedicated to the study of VRP; we have compiled here a great deal of information about it for public access: technical reports, many different variants of the problem, alternative algorithms and techniques for solving it, some well-known instances of the problem, the best-so-far solutions for those instances, bibliography, related links… (Source: http://plato.asu.edu)

References in zbMATH (referenced in 966 articles )

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  1. Adamo, Tommaso; Ghiani, Gianpaolo; Guerriero, Emanuela: An enhanced lower bound for the time-dependent travelling salesman problem (2020)
  2. Agarwal, Yogesh Kumar; Venkateshan, Prahalad: A new model for the asymmetric vehicle routing problem with simultaneous pickup and deliveries (2020)
  3. Aldana-Galván, I.; Catana-Salazar, J. C.; Díaz-Báñez, J. M.; Duque, F.; Fabila-Monroy, R.; Heredia, M. A.; Ramírez-Vigueras, A.; Urrutia, J.: On optimal coverage of a tree with multiple robots (2020)
  4. Alvarez, Aldair; Cordeau, Jean-François; Jans, Raf; Munari, Pedro; Morabito, Reinaldo: Formulations, branch-and-cut and a hybrid heuristic algorithm for an inventory routing problem with perishable products (2020)
  5. Bortfeldt, Andreas; Yi, Junmin: The split delivery vehicle routing problem with three-dimensional loading constraints (2020)
  6. Brandão, José: A memory-based iterated local search algorithm for the multi-depot open vehicle routing problem (2020)
  7. Bruni, M. E.; Beraldi, P.; Khodaparasti, S.: A hybrid reactive GRASP heuristic for the risk-averse (k)-traveling repairman problem with profits (2020)
  8. Chitsaz, Masoud; Cordeau, Jean-François; Jans, Raf: A branch-and-cut algorithm for an assembly routing problem (2020)
  9. Christiansen, Marielle; Hellsten, Erik; Pisinger, David; Sacramento, David; Vilhelmsen, Charlotte: Liner shipping network design (2020)
  10. Eshragh, Ali; Esmaeilbeigi, Rasul; Middleton, Richard: An analytical bound on the fleet size in vehicle routing problems: a dynamic programming approach (2020)
  11. Eshtehadi, Reza; Demir, Emrah; Huang, Yuan: Solving the vehicle routing problem with multi-compartment vehicles for city logistics (2020)
  12. Fachini, Ramon Faganello; Armentano, Vinícius Amaral: Exact and heuristic dynamic programming algorithms for the traveling salesman problem with flexible time windows (2020)
  13. Factorovich, Pablo; Méndez-Díaz, Isabel; Zabala, Paula: Pickup and delivery problem with incompatibility constraints (2020)
  14. Fernandes, I. F. C.; Goldbarg, E. F. G.; Maia, S. M. D. M.; Goldbarg, M. C.: Empirical study of exact algorithms for the multi-objective spanning tree (2020)
  15. Florio, Alexandre M.; Hartl, Richard F.; Minner, Stefan: Optimal a priori tour and restocking policy for the single-vehicle routing problem with stochastic demands (2020)
  16. Fotio Tiotsop, Lohic; Servetti, Antonio; Masala, Enrico: An integer linear programming model for efficient scheduling of UGV tasks in precision agriculture under human supervision (2020)
  17. Gansterer, Margaretha; Hartl, Richard F.: Shared resources in collaborative vehicle routing (2020)
  18. Glize, Estèle; Roberti, Roberto; Jozefowiez, Nicolas; Ngueveu, Sandra Ulrich: Exact methods for mono-objective and bi-objective multi-vehicle covering tour problems (2020)
  19. Gnegel, Fabian; Fügenschuh, Armin: An iterative graph expansion approach for the scheduling and routing of airplanes (2020)
  20. Hintsch, Timo; Irnich, Stefan: Exact solution of the soft-clustered vehicle-routing problem (2020)

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Further publications can be found at: http://neo.lcc.uma.es/vrp/bibliography-on-vrp/