IBM® ILOG® CPLEX® offers C, C++, Java, .NET, and Python libraries that solve linear programming (LP) and related problems. Specifically, it solves linearly or quadratically constrained optimization problems where the objective to be optimized can be expressed as a linear function or a convex quadratic function. The variables in the model may be declared as continuous or further constrained to take only integer values.

References in zbMATH (referenced in 1668 articles , 1 standard article )

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  1. Glenn, Paul; Menasco, William W.; Morrell, Kayla; Morse, Matthew J.: MICC: a tool for computing short distances in the curve complex (2017)
  2. Adasme, Pablo; Lisser, Abdel: Uplink scheduling for joint wireless orthogonal frequency and time division multiple access networks (2016)
  3. Akkan, Can; Erdem Külünk, M.; Koçaş, Cenk: Finding robust timetables for project presentations of student teams (2016)
  4. Alabdulmohsin, Ibrahim; Cisse, Moustapha; Gao, Xin; Zhang, Xiangliang: Large margin classification with indefinite similarities (2016)
  5. Ambrosino, Daniela; Sciomachen, Anna: A capacitated hub location problem in freight logistics multimodal networks (2016)
  6. Arıkan, Uğur; Gürel, Sinan; Aktürk, M.Selim: Integrated aircraft and passenger recovery with cruise time controllability (2016)
  7. Azizi, Nader; Chauhan, Satyaveer; Salhi, Said; Vidyarthi, Navneet: The impact of hub failure in hub-and-spoke networks: mathematical formulations and solution techniques (2016)
  8. Bai, Yanqin; Liang, Renli; Yang, Zhouwang: Splitting augmented Lagrangian method for optimization problems with a cardinality constraint and semicontinuous variables (2016)
  9. Bang, Sungwan; Eo, Soo-Heang; Cho, Yong Mee; Jhun, Myoungshic; Cho, HyungJun: Non-crossing weighted kernel quantile regression with right censored data (2016)
  10. Barketau, Maksim; Pesch, Erwin; Shafransky, Yakov: Scheduling dedicated jobs with variative processing times (2016)
  11. Belotti, Pietro; Bonami, Pierre; Fischetti, Matteo; Lodi, Andrea; Monaci, Michele; Nogales-Gómez, Amaya; Salvagnin, Domenico: On handling indicator constraints in mixed integer programming (2016)
  12. Billionnet, Alain; Elloumi, Sourour; Lambert, Amélie: Exact quadratic convex reformulations of mixed-integer quadratically constrained problems (2016)
  13. Blum, Christian; Blesa, Maria J.: Construct, merge, solve and adapt: application to the repetition-free longest common subsequence problem (2016)
  14. Blum, Christian; Raidl, Günther R.: Computational performance evaluation of two integer linear programming models for the minimum common string partition problem (2016)
  15. Boland, Natashia; Clement, Riley; Waterer, Hamish: A bucket indexed formulation for nonpreemptive single machine scheduling problems (2016)
  16. Borndörfer, Ralf; Schenker, Sebastian; Skutella, Martin; Strunk, Timo: PolySCIP (2016)
  17. Branda, Martin: Mean-value at risk portfolio efficiency: approaches based on data envelopment analysis models with negative data and their empirical behaviour (2016)
  18. Brás, Carmo; Eichfelder, Gabriele; Júdice, Joaquim: Copositivity tests based on the linear complementarity problem (2016)
  19. Braun, Gábor; Pokutta, Sebastian: A polyhedral characterization of border bases (2016)
  20. Buchheim, Christoph; De Santis, Marianna; Lucidi, Stefano; Rinaldi, Francesco; Trieu, Long: A feasible active set method with reoptimization for convex quadratic mixed-integer programming (2016)

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