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 1676 articles , 1 standard article )

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

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