VRP

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 1069 articles )

Showing results 1 to 20 of 1069.
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  1. Chen, Ye; Marković, Nikola; Ryzhov, Ilya O.; Schonfeld, Paul: Data-driven robust resource allocation with monotonic cost functions (2022)
  2. de Lima, Vinícius L.; Alves, Cláudio; Clautiaux, François; Iori, Manuel; Valério de Carvalho, José M.: Arc flow formulations based on dynamic programming: theoretical foundations and applications (2022)
  3. Morapitiye, Sunil; Kis, Tamás: Strong cuts from compatibility relations for the dial-a-ride problem (2022)
  4. Abdullahi, Hassana; Reyes-Rubiano, Lorena; Ouelhadj, Djamila; Faulin, Javier; Juan, Angel A.: Modelling and multi-criteria analysis of the sustainability dimensions for the green vehicle routing problem (2021)
  5. Afshani, Peyman; de Berg, Mark; Buchin, Kevin; Gao, Jie; Löffler, Maarten; Nayyeri, Amir; Raichel, Benjamin; sarkar, Rik; Wang, Haotian; Yang, Hao-Tsung: Approximation algorithms for multi-robot patrol-scheduling with min-max latency (2021)
  6. Ali, Ousmane; Côté, Jean-François; Coelho, Leandro C.: Models and algorithms for the delivery and installation routing problem (2021)
  7. Bakker, Steffen J.; Wang, Akang; Gounaris, Chrysanthos E.: Vehicle routing with endogenous learning: application to offshore plug and abandonment campaign planning (2021)
  8. Baller, Annelieke C.; Dabia, Said; Desaulniers, Guy; Dullaert, Wout E. H.: The inventory routing problem with demand moves (2021)
  9. Behrend, Moritz; Meisel, Frank; Fagerholt, Kjetil; Andersson, Henrik: A multi-period analysis of the integrated item-sharing and crowdshipping problem (2021)
  10. Ben Ticha, Hamza; Absi, Nabil; Feillet, Dominique; Quilliot, Alain; Van Woensel, Tom: The time-dependent vehicle routing problem with time windows and road-network information (2021)
  11. Beraldi, Patrizia; De Maio, Annarita; Laganà, Demetrio; Violi, Antonio: A pick-up and delivery problem for logistics e-marketplace services (2021)
  12. Bianchessi, Nicola; Irnich, Stefan; Tilk, Christian: A branch-price-and-cut algorithm for the capacitated multiple vehicle traveling purchaser problem with unitary demand (2021)
  13. Bordón, Maximiliano R.; Montagna, Jorge M.; Corsano, Gabriela: Solution approaches for solving the log transportation problem (2021)
  14. Brandstätter, Christian: A metaheuristic algorithm and structured analysis for the Line-haul Feeder vehicle routing problem with time windows (2021)
  15. Bruglieri, M.; Mancini, S.; Peruzzini, R.; Pisacane, O.: The multi-period multi-trip container drayage problem with release and due dates (2021)
  16. Carrabs, Francesco: A biased random-key genetic algorithm for the set orienteering problem (2021)
  17. Ceselli, Alberto; Felipe, Ángel; Ortuño, M. Teresa; Righini, Giovanni; Tirado, Gregorio: A branch-and-cut-and-price algorithm for the electric vehicle routing problem with multiple technologies (2021)
  18. Charalambopoulos, Nikolaos; Nearchou, Andreas C.: Ship routing using genetic algorithms (2021)
  19. Chen, Lu; Chen, Yuyi; Langevin, André: An inverse optimization approach for a capacitated vehicle routing problem (2021)
  20. Cinar, Ahmet; Salman, F. Sibel; Bozkaya, Burcin: Prioritized single nurse routing and scheduling for home healthcare services (2021)

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