TSPLIB

TSPLIB is a library of sample instances for the TSP (and related problem) from various sources and of various types. Instances of the following problem classes are available. Symmetric traveling salesman problem (TSP) Hamiltonian cycle problem (HCP) Asymmetric traveling salesman problem (ATSP) Sequential ordering problem (SOP) Capacitated vehicle routing problem (CVRP)


References in zbMATH (referenced in 580 articles , 1 standard article )

Showing results 1 to 20 of 580.
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  1. Álvarez-Miranda, Eduardo; Luipersbeck, Martin; Sinnl, Markus: Gotta (efficiently) catch them all: Pokémon GO meets orienteering problems (2018)
  2. Archetti, Claudia; Feillet, Dominique; Mor, Andrea; Speranza, M. Grazia: An iterated local search for the traveling salesman problem with release dates and completion time minimization (2018)
  3. Balma, Ali; Salem, Safa Ben; Mrad, Mehdi; Ladhari, Talel: Strong multi-commodity flow formulations for the asymmetric traveling salesman problem (2018)
  4. Beek, Onne; Raa, Birger; Dullaert, Wout; Vigo, Daniele: An efficient implementation of a static move descriptor-based local search heuristic (2018)
  5. Bernardino, Raquel; Paias, Ana: Solving the family traveling salesman problem (2018)
  6. Burger, M.; Su, Z.; De Schutter, B.: A node current-based 2-index formulation for the fixed-destination multi-depot travelling salesman problem (2018)
  7. Diarrassouba, Ibrahima; Labidi, Mohamed Khalil; Mahjoub, Ali Ridha: A hybrid optimization approach for the Steiner $k$-connected network design problem (2018)
  8. 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)
  9. Goldbarg, Marco C.; Goldbarg, Elizabeth F. G.; Luna, Henrique P. L.; Menezes, Matheus S.; Corrales, Lucas: Integer programming models and linearizations for the traveling car renter problem (2018)
  10. Kobeaga, Gorka; Merino, María; Lozano, Jose A.: An efficient evolutionary algorithm for the orienteering problem (2018)
  11. Lu, Yongliang; Benlic, Una; Wu, Qinghua: Multi-restart iterative search for the pickup and delivery traveling salesman problem with FIFO loading (2018)
  12. Martins, Daniel; Vianna, Gabriel M.; Rosseti, Isabel; Martins, Simone L.; Plastino, Alexandre: Making a state-of-the-art heuristic faster with data mining (2018)
  13. Nam, N. M.; Geremew, W.; Reynolds, S.; Tran, T.: Nesterov’s smoothing technique and minimizing differences of convex functions for hierarchical clustering (2018)
  14. Robinson, Jeffrey A.; Vrbsky, Susan V.; Hong, Xiaoyan; Eddy, Brian P.: Analysis of a high-performance TSP solver on the GPU (2018)
  15. Saleh Farham, Mohammad; Süral, Haldun; Iyigun, Cem: Generalization of the restricted planar location problems: unified metaheuristic algorithms (2018)
  16. Stidsen, Thomas; Andersen, Kim Allan: A hybrid approach for biobjective optimization (2018)
  17. Van Cauwelaert, Sascha; Lombardi, Michele; Schaus, Pierre: How efficient is a global constraint in practice? A fair experimental framework (2018)
  18. Adamo, Tommaso; Ghiani, Gianpaolo; Grieco, Antonio; Guerriero, Emanuela; Manni, Emanuele: MIP neighborhood synthesis through semantic feature extraction and automatic algorithm configuration (2017)
  19. Baldacci, Roberto; Hill, Alessandro; Hoshino, Edna A.; Lim, Andrew: Pricing strategies for capacitated ring-star problems based on dynamic programming algorithms (2017)
  20. Barbosa, Eduardo Batista de Moraes; Senne, Edson Luiz França: Improving the fine-tuning of metaheuristics: an approach combining design of experiments and racing algorithms (2017)

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Further publications can be found at: http://comopt.ifi.uni-heidelberg.de/publications/index.html