AMPL is a comprehensive and powerful algebraic modeling language for linear and nonlinear optimization problems, in discrete or continuous variables. Developed at Bell Laboratories, AMPL lets you use common notation and familiar concepts to formulate optimization models and examine solutions, while the computer manages communication with an appropriate solver. AMPL’s flexibility and convenience render it ideal for rapid prototyping and model development, while its speed and control options make it an especially efficient choice for repeated production runs.

References in zbMATH (referenced in 537 articles , 2 standard articles )

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  1. Colapinto, Cinzia; Jayaraman, Raja; La Torre, Davide: Goal programming models for managerial strategic decision making (2020)
  2. Andersson, Joel A. E.; Gillis, Joris; Horn, Greg; Rawlings, James B.; Diehl, Moritz: CasADi: a software framework for nonlinear optimization and optimal control (2019)
  3. Gambella, Claudio; Maggioni, Francesca; Vigo, Daniele: A stochastic programming model for a tactical solid waste management problem (2019)
  4. Ledzewicz, Urszula; Maurer, Helmut; Schättler, Heinz: Optimal combined radio- and anti-angiogenic cancer therapy (2019)
  5. Pereira Coutinho, Walton; Fliege, Jörg; Battarra, Maria: Glider routing and trajectory optimisation in disaster assessment (2019)
  6. Petra, Cosmin G.; Chiang, Naiyuan; Anitescu, Mihai: A structured quasi-Newton algorithm for optimizing with incomplete Hessian information (2019)
  7. Torgovitsky, Alexander: Partial identification by extending subdistributions (2019)
  8. Amaya Moreno, Liana; Fügenschuh, Armin; Kaier, Anton; Schlobach, Swen: A nonlinear model for vertical free-flight trajectory planning (2018)
  9. Arreckx, Sylvain; Orban, Dominique: A regularized factorization-free method for equality-constrained optimization (2018)
  10. Baydin, Atılım Güneş; Pearlmutter, Barak A.; Radul, Alexey Andreyevich; Siskind, Jeffrey Mark: Automatic differentiation in machine learning: a survey (2018)
  11. Bruglieri, Maurizio; Pezzella, Ferdinando; Pisacane, Ornella: A two-phase optimization method for a multiobjective vehicle relocation problem in electric carsharing systems (2018)
  12. Cafieri, Sonia; Cellier, Loïc; Messine, Frédéric; Omheni, Riadh: Combination of optimal control approaches for aircraft conflict avoidance via velocity regulation (2018)
  13. Cafieri, Sonia; D’Ambrosio, Claudia: Feasibility pump for aircraft deconfliction with speed regulation (2018)
  14. Camponogara, Eduardo; Guardini, Luiz Alberto; de Assis, Leonardo Salsano: Scheduling pumpoff operations in onshore oilfields with electric-power constraints and variable cycle time (2018)
  15. Carrizosa, Emilio; Guerrero, Vanesa; Romero Morales, Dolores: On mathematical optimization for the visualization of frequencies and adjacencies as rectangular maps (2018)
  16. de Pinho, Maria do Rosário; Maurer, Helmut; Zidani, Hasnaa: Optimal control of normalized SIMR models with vaccination and treatment (2018)
  17. Gay, David M.: Revisiting expression representations for nonlinear AMPL models (2018)
  18. Gelashvili, Koba; Khutsishvili, Irina; Gorgadze, Luka; Alkhazishvili, Lela: Speeding up the convergence of the Polyak’s heavy ball algorithm (2018)
  19. Göllmann, Laurenz; Maurer, Helmut: Optimal control problems with time delays: two case studies in biomedicine (2018)
  20. Hossain, Shahadat; Hakim Mithila, Nasrin: Pattern graph for sparse Hessian matrix (2018)

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