CPLEX
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.
Keywords for this software
References in zbMATH (referenced in 2281 articles , 1 standard article )
Showing results 1 to 20 of 2281.
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- Ahmadi, Amir Ali; Majumdar, Anirudha: DSOS and SDSOS optimization: more tractable alternatives to sum of squares and semidefinite optimization (2019)
- Andersson, Joel A. E.; Gillis, Joris; Horn, Greg; Rawlings, James B.; Diehl, Moritz: CasADi: a software framework for nonlinear optimization and optimal control (2019)
- Becker, Henrique; Buriol, Luciana S.: An empirical analysis of exact algorithms for the unbounded knapsack problem (2019)
- Bonami, Pierre; Lodi, Andrea; Schweiger, Jonas; Tramontani, Andrea: Solving quadratic programming by cutting planes (2019)
- Brech, Claus-Henning; Ernst, Andreas; Kolisch, Rainer: Scheduling medical residents’ training at university hospitals (2019)
- Briskorn, Dirk; Dienstknecht, Michael: Mixed-integer programming models for tower crane selection and positioning with respect to mutual interference (2019)
- Castro, Jordi; González, José A.: A linear optimization-based method for data privacy in statistical tabular data (2019)
- Ceselli, Alberto; Fiore, Marco; Premoli, Marco; Secci, Stefano: Optimized assignment patterns in mobile edge cloud networks (2019)
- Chassein, André; Dokka, Trivikram; Goerigk, Marc: Algorithms and uncertainty sets for data-driven robust shortest path problems (2019)
- Clautiaux, François; Guillot, Jérémy; Pesneau, Pierre: Exact approaches for solving a covering problem with capacitated subtrees (2019)
- Della Croce, Federico; Pferschy, Ulrich; Scatamacchia, Rosario: New exact approaches and approximation results for the penalized knapsack problem (2019)
- de Matta, Renato: Product costing in the strategic formation of a supply chain (2019)
- Ecker, Grit; Yuan, Di; Koster, Arie M. C. A.; Schmeink, Anke: Accurate optimization models for interference constrained bandwidth allocation in cellular networks (2019)
- Elloumi, Sourour; Lambert, Amélie: Global solution of non-convex quadratically constrained quadratic programs (2019)
- Fanjul-Peyro, Luis; Ruiz, Rubén; Perea, Federico: Reformulations and an exact algorithm for unrelated parallel machine scheduling problems with setup times (2019)
- Gambella, Claudio; Maggioni, Francesca; Vigo, Daniele: A stochastic programming model for a tactical solid waste management problem (2019)
- Ghasemi Saghand, Payman; Charkhgard, Hadi; Kwon, Changhyun: A branch-and-bound algorithm for a class of mixed integer linear maximum multiplicative programs: a bi-objective optimization approach (2019)
- Grimm, Veronika; Kleinert, Thomas; Liers, Frauke; Schmidt, Martin; Zöttl, Gregor: Optimal price zones of electricity markets: a mixed-integer multilevel model and global solution approaches (2019)
- Györgyi, Péter; Kis, Tamás: A probabilistic approach to pickup and delivery problems with time window uncertainty (2019)
- Hamdan, Bayan; Diabat, Ali: A two-stage multi-echelon stochastic blood supply chain problem (2019)