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 616 articles )

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  1. Sundar, Kaarthik; Rathinam, Sivakumar: Multiple depot ring star problem: a polyhedral study and an exact algorithm (2017)
  2. Wang, Xingyin; Poikonen, Stefan; Golden, Bruce: The vehicle routing problem with drones: several worst-case results (2017)
  3. Afifi, Sohaib; Dang, Duc-Cuong; Moukrim, Aziz: Heuristic solutions for the vehicle routing problem with time windows and synchronized visits (2016)
  4. Andreatta, G.; Casula, M.; De Francesco, C.; De Giovanni, L.: A branch-and-price based heuristic for the stochastic vehicle routing problem with hard time windows (2016)
  5. Archetti, Claudia; Corberán, Ángel; Plana, Isaac; Sanchis, José M.; Speranza, M.Grazia: A branch-and-cut algorithm for the orienteering arc routing problem (2016)
  6. Archetti, Claudia; Savelsbergh, Martin; Speranza, M.Grazia: The vehicle routing problem with occasional drivers (2016)
  7. Baklagis, D.G.; Dikas, G.; Minis, I.: The team orienteering pick-up and delivery problem with time windows and its applications in fleet sizing (2016)
  8. Bautzer, Ana; Gouveia, Luís; Paias, Ana; Pires, José Manuel: Models for a Steiner multi-ring network design problem with revenues (2016)
  9. Brandão, José: A deterministic iterated local search algorithm for the vehicle routing problem with backhauls (2016)
  10. Breunig, U.; Schmid, V.; Hartl, R.F.; Vidal, T.: A large neighbourhood based heuristic for two-echelon routing problems (2016)
  11. Bui, Quoc Trung; Deville, Yves; Pham, Quang Dung: Exact methods for solving the elementary shortest and longest path problems (2016)
  12. Cattaruzza, Diego; Absi, Nabil; Feillet, Dominique: Vehicle routing problems with multiple trips (2016)
  13. Chakrabarty, Deeparnab; Swamy, Chaitanya: Facility location with client latencies: LP-based techniques for minimum-latency problems (2016)
  14. Cortinhal, Maria João; Mourão, Maria C^andida; Nunes, Ana Catarina: Local search heuristics for sectoring routing in a household waste collection context (2016)
  15. DellAmico, Mauro; Iori, Manuel; Novellani, Stefano; Stützle, Thomas: A destroy and repair algorithm for the bike sharing rebalancing problem (2016)
  16. Desaulniers, Guy; Errico, Fausto; Irnich, Stefan; Schneider, Michael: Exact algorithms for electric vehicle-routing problems with time windows (2016)
  17. Di Puglia Pugliese, Luigi; Guerriero, Francesca: On the shortest path problem with negative cost cycles (2016)
  18. Di Puglia Pugliese, Luigi; Guerriero, Francesca; Zorbas, Dimitrios; Razafindralambo, Tahiry: Modelling the mobile target covering problem using flying drones (2016)
  19. Dominguez, Oscar; Guimarans, Daniel; Juan, Angel A.; de la Nuez, Ignacio: A biased-randomised large neighbourhood search for the two-dimensional vehicle routing problem with backhauls (2016)
  20. Dominguez, Oscar; Juan, Angel A.; Barrios, Barry; Faulin, Javier; Agustin, Alba: Using biased randomization for solving the two-dimensional loading vehicle routing problem with heterogeneous fleet (2016)

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