LEMON

LEMON – an Open Source C++ Graph Template Library. This paper introduces LEMON, a generic open source C++ library providing easy-to-use and efficient implementations of graph and network algorithms and related data structures. The basic design concepts, features, and performance of LEMON are compared with similar software packages, namely BGL (Boost Graph Library) and LEDA. LEMON turned out to be a viable alternative to these widely used libraries, and our benchmarks show that it typically outperforms them in efficiency. (Source: http://plato.asu.edu)


References in zbMATH (referenced in 48 articles , 1 standard article )

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  1. Assunção, Lucas; Mateus, Geraldo Robson: Coupling feasibility pump and large neighborhood search to solve the Steiner team orienteering problem (2021)
  2. Carrabs, Francesco: A biased random-key genetic algorithm for the set orienteering problem (2021)
  3. Castro, Jordi; Nasini, Stefano: A specialized interior-point algorithm for huge minimum convex cost flows in bipartite networks (2021)
  4. Ekim, Tınaz; Shalom, Mordechai; Şeker, Oylum: The complexity of subtree intersection representation of chordal graphs and linear time chordal graph generation (2021)
  5. Graf, Benjamin: Preemptive stacker crane problem: extending tree-based properties and construction heuristics (2021)
  6. Miyazawa, Flávio K.; Moura, Phablo F. S.; Ota, Matheus J.; Wakabayashi, Yoshiko: Partitioning a graph into balanced connected classes: formulations, separation and experiments (2021)
  7. Ren, Chaofeng; Zhi, Xiaodong; Pu, Yuchi; Zhang, Fuqiang: A multi-scale UAV image matching method applied to large-scale landslide reconstruction (2021)
  8. Song, Guopeng; Kis, Tamás; Leus, Roel: Polyhedral results and branch-and-cut for the resource loading problem (2021)
  9. Buckow, Jan-Niklas; Graf, Benjamin; Knust, Sigrid: The exponential multi-insertion neighborhood for the vehicle routing problem with unit demands (2020)
  10. Pessoa, Artur; Sadykov, Ruslan; Uchoa, Eduardo; Vanderbeck, François: A generic exact solver for vehicle routing and related problems (2020)
  11. Arakaki, Rafael Kendy; Usberti, Fábio Luiz: An efficiency-based path-scanning heuristic for the capacitated arc routing problem (2019)
  12. Chassein, André; Dokka, Trivikram; Goerigk, Marc: Algorithms and uncertainty sets for data-driven robust shortest path problems (2019)
  13. Horváth, Markó; Kis, Tamás: Computing strong lower and upper bounds for the integrated multiple-depot vehicle and crew scheduling problem with branch-and-price (2019)
  14. Koza, David Franz: Liner shipping service scheduling and cargo allocation (2019)
  15. Molnár-Szipai, Richárd; Varga, Anita: Integrating combinatorial algorithms into a linear programming solver (2019)
  16. Pothen, Alex; Ferdous, S. M.; Manne, Fredrik: Approximation algorithms in combinatorial scientific computing (2019)
  17. Samer, Phillippe; Cavalcante, Evellyn; Urrutia, Sebastián; Oppen, Johan: The matching relaxation for a class of generalized set partitioning problems (2019)
  18. Sanders, Peter; Mehlhorn, Kurt; Dietzfelbinger, Martin; Dementiev, Roman: Sequential and parallel algorithms and data structures. The basic toolbox (2019)
  19. Ahat, Betül; Ekim, Tınaz; Taşkın, Z. Caner: Integer programming formulations and Benders decomposition for the maximum induced matching problem (2018)
  20. Arakaki, Rafael Kendy; Usberti, Fábio Luiz: Hybrid genetic algorithm for the open capacitated arc routing problem (2018)

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