Concorde

Concorde is a computer code for the symmetric traveling salesman problem (TSP) and some related network optimization problems. The code is written in the ANSI C programming language and it is available for academic research use; for other uses, contact William Cook for licensing options. Concorde’s TSP solver has been used to obtain the optimal solutions to 106 of the 110 TSPLIB instances; the largest having 85,900 cities. The Concorde callable library includes over 700 functions permitting users to create specialized codes for TSP-like problems. All Concorde functions are thread-safe for programming in shared-memory parallel environments; the main TSP solver includes code for running over networks of UNIX workstations.


References in zbMATH (referenced in 241 articles , 1 standard article )

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  1. Álvarez-Miranda, Eduardo; Luipersbeck, Martin; Sinnl, Markus: Gotta (efficiently) catch them all: Pokémon GO meets orienteering problems (2018)
  2. Burger, M.; Su, Z.; De Schutter, B.: A node current-based 2-index formulation for the fixed-destination multi-depot travelling salesman problem (2018)
  3. Delorme, Maxence; Iori, Manuel; Martello, Silvano: BPPLIB: a library for bin packing and cutting stock problems (2018)
  4. Diamond, S.; Takapoui, R.; Boyd, S.: A general system for heuristic minimization of convex functions over non-convex sets (2018)
  5. Domínguez-Martín, Bencomo; Rodríguez-Martín, Inmaculada; Salazar-González, Juan-José: The driver and vehicle routing problem (2018)
  6. Ferrer, José M.; Martín-Campo, F. Javier; Ortuño, M. Teresa; Pedraza-Martínez, Alfonso J.; Tirado, Gregorio; Vitoriano, Begoña: Multi-criteria optimization for last mile distribution of disaster relief aid: test cases and applications (2018)
  7. Gao, Zhihan: On the metric $s$-$t$ path traveling salesman problem (2018)
  8. Klapp, Mathias A.; Erera, Alan L.; Toriello, Alejandro: The dynamic dispatch waves problem for same-day delivery (2018)
  9. Kobeaga, Gorka; Merino, María; Lozano, Jose A.: An efficient evolutionary algorithm for the orienteering problem (2018)
  10. Kumar, Santosh; Munapo, Elias; Lesaoana, ’Maseka; Nyamugure, Philimon: A minimum spanning tree based heuristic for the travelling salesman tour (2018)
  11. Lahyani, Rahma; Coelho, Leandro C.; Renaud, Jacques: Alternative formulations and improved bounds for the multi-depot fleet size and mix vehicle routing problem (2018)
  12. Lancia, Giuseppe; Serafini, Paolo: Compact extended linear programming models (2018)
  13. Martins de Sá, Elisangela; Morabito, Reinaldo; de Camargo, Ricardo Saraiva: Benders decomposition applied to a robust multiple allocation incomplete hub location problem (2018)
  14. Nesello, Vitor; Subramanian, Anand; Battarra, Maria; Laporte, Gilbert: Exact solution of the single-machine scheduling problem with periodic maintenances and sequence-dependent setup times (2018)
  15. Stidsen, Thomas; Andersen, Kim Allan: A hybrid approach for biobjective optimization (2018)
  16. Bartlett, Mark; Cussens, James: Integer linear programming for the Bayesian network structure learning problem (2017)
  17. Bliznets, Ivan; Fomin, Fedor V.; Golovach, Petr A.; Karpov, Nikolay; Kulikov, Alexander S.; Saurabh, Saket: Parameterized complexity of superstring problems (2017)
  18. Borst, Sem; Bradonjić, Milan: Scaling laws for maximum coloring of random geometric graphs (2017)
  19. Bouzid, Mouaouia Cherif; Aït Haddadene, Hacene; Salhi, Said: An integration of Lagrangian split and VNS: the case of the capacitated vehicle routing problem (2017)
  20. Burke, Edmund K.; Bykov, Yuri: The late acceptance hill-climbing heuristic (2017)

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