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 319 articles , 1 standard article )

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  1. Chen, Sheng-I; Tseng, Yen-Che: A partitioning column approach for solving LED sorter manipulator path planning problems (2022)
  2. Santini, Alberto; Viana, Ana; Klimentova, Xenia; Pedroso, João Pedro: The probabilistic travelling salesman problem with crowdsourcing (2022)
  3. Taillard, Éric D.: A linearithmic heuristic for the travelling salesman problem (2022)
  4. Cohen, Eldan; Beck, J. Christopher: Heavy-tails and randomized restarting beam search in goal-oriented neural sequence decoding (2021)
  5. Eifler, Leon; Gleixner, Ambros: A computational status update for exact rational mixed integer programming (2021)
  6. Graf, Benjamin: Preemptive stacker crane problem: extending tree-based properties and construction heuristics (2021)
  7. Haddadi, Salim: Iterated local search for consecutive block minimization (2021)
  8. Hintsch, Timo: Large multiple neighborhood search for the soft-clustered vehicle-routing problem (2021)
  9. Hougardy, Stefan; Zhong, Xianghui: Hard to solve instances of the Euclidean traveling salesman problem (2021)
  10. Ozden, S. G.; Smith, A. E.; Gue, K. R.: A computational software system to design order picking warehouses (2021)
  11. Sun, Yuan; Ernst, Andreas; Li, Xiaodong; Weiner, Jake: Generalization of machine learning for problem reduction: a case study on travelling salesman problems (2021)
  12. Wolfinger, David; Salazar-González, Juan-José: The pickup and delivery problem with split loads and transshipments: a branch-and-cut solution approach (2021)
  13. 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)
  14. Khachay, Michael; Neznakhina, Katherine: Complexity and approximability of the Euclidean generalized traveling salesman problem in grid clusters (2020)
  15. Moreno, Alfredo; Munari, Pedro; Alem, Douglas: Decomposition-based algorithms for the crew scheduling and routing problem in road restoration (2020)
  16. Sahai, Tuhin: Dynamical systems theory and algorithms for NP-hard problems (2020)
  17. Soares, Leonardo C. R.; Reinsma, Jordi Alves; Nascimento, Luis H. L.; Carvalho, Marco A. M.: Heuristic methods to consecutive block minimization (2020)
  18. Badger, Matthew; Naples, Lisa; Vellis, Vyron: Hölder curves and parameterizations in the Analyst’s traveling salesman theorem (2019)
  19. da Silva, Tiago Tiburcio; Chaves, Antônio Augusto; Yanasse, Horacio Hideki; Luna, Henrique Pacca Loureiro: The multicommodity traveling salesman problem with priority prizes: a mathematical model and metaheuristics (2019)
  20. Date, Prasanna; Patton, Robert; Schuman, Catherine; Potok, Thomas: Efficiently embedding QUBO problems on adiabatic quantum computers (2019)

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