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 2551 articles , 1 standard article )

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  1. Alfieri, Arianna; Matta, Andrea; Pastore, Erica: The time buffer approximated buffer allocation problem: a row-column generation approach (2020)
  2. Aparicio, Juan; Kapelko, Magdalena; Monge, Juan F.: A well-defined composite indicator: an application to corporate social responsibility (2020)
  3. Arbex Valle, Cristiano; Beasley, John E.: Order batching using an approximation for the distance travelled by pickers (2020)
  4. Atashi Khoei, Arsham; Süral, Haldun; Tural, Mustafa Kemal: Multi-facility Green Weber problem (2020)
  5. Basso, S.; Ceselli, Alberto; Tettamanzi, Andrea: Random sampling and machine learning to understand good decompositions (2020)
  6. Bautista-Valhondo, Joaquín; Alfaro-Pozo, Rocío: Mixed integer linear programming models for flow shop scheduling with a demand plan of job types (2020)
  7. Bayless, Sam; Kodirov, Nodir; Iqbal, Syed M.; Beschastnikh, Ivan; Hoos, Holger H.; Hu, Alan J.: Scalable constraint-based virtual data center allocation (2020)
  8. Bereg, Sergey; Mojica, Luis Gerardo; Morales, Linda; Sudborough, Hal: Constructing permutation arrays using partition and extension (2020)
  9. Berger, J.; Lo, N.; Barkaoui, M.: QUEST -- a new quadratic decision model for the multi-satellite scheduling problem (2020)
  10. Bertsimas, Dimitris; Lamperski, Jourdain; Pauphilet, Jean: Certifiably optimal sparse inverse covariance estimation (2020)
  11. Bettiol, Enrico; Létocart, Lucas; Rinaldi, Francesco; Traversi, Emiliano: A conjugate direction based simplicial decomposition framework for solving a specific class of dense convex quadratic programs (2020)
  12. Borenich, Andrea; Greistorfer, Peter; Reimann, Marc: Model-based production cost estimation to support bid processes: an automotive case study (2020)
  13. Borghini, Fabrizio; Méndez-Díaz, Isabel; Zabala, Paula: An exact algorithm for the edge coloring by total labeling problem (2020)
  14. Briheche, Yann; Barbaresco, Frederic; Bennis, Fouad; Chablat, Damien: Branch-and-bound method for just-in-time optimization of radar search patterns (2020)
  15. Briskorn, Dirk; Zey, Lennart: Interference aware scheduling of triple-crossover-cranes (2020)
  16. Chen, Qian Matteo; Finzi, Alberto; Mancini, Toni; Melatti, Igor; Tronci, Enrico: MILP, pseudo-Boolean, and OMT solvers for optimal fault-tolerant placements of relay nodes in mission critical wireless networks (2020)
  17. Coey, Chris; Lubin, Miles; Vielma, Juan Pablo: Outer approximation with conic certificates for mixed-integer convex problems (2020)
  18. Costalonga, João Paulo: Toroidal boards and code covering (2020)
  19. Dahlbeck, Mirko; Fischer, Anja; Fischer, Frank: Decorous combinatorial lower bounds for row layout problems (2020)
  20. D’Ambrosio, Claudia; Liberti, Leo; Poirion, Pierre-Louis; Vu, Ky: Random projections for quadratic programs (2020)

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