Benchmarking optimization software with COPS. We are continuing the development of COPS, a large-scale Constrained Optimization Problem Set. The primary purpose of this collection is to provide difficult test cases for optimization software. Problems in the current version of the collection come from fluid dynamics, population dynamics, optimal design, mesh smoothing, and optimal control. For each problem we provide a short description of the problem, notes on the formulation of the problem, and results of computational experiments with general optimization solvers. Each problem has been implemented in AMPL. The models from COPS 2.0 are also available in GAMS, courtesy of GAMS Development Corporation.

References in zbMATH (referenced in 20 articles )

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  1. Qiu, Songqiang; Chen, Zhongwen: A globally convergent penalty-free method for optimization with equality constraints and simple bounds (2016)
  2. Curtis, Frank E.; Jiang, Hao; Robinson, Daniel P.: An adaptive augmented Lagrangian method for large-scale constrained optimization (2015)
  3. Gill, Philip E.; Wong, Elizabeth: Methods for convex and general quadratic programming (2015)
  4. Armand, Paul; Benoist, Joël; Omheni, Riadh; Pateloup, Vincent: Study of a primal-dual algorithm for equality constrained minimization (2014)
  5. Bussieck, Michael R.; Dirkse, Steven P.; Vigerske, Stefan: PAVER 2.0: an open source environment for automated performance analysis of benchmarking data (2014)
  6. Kirches, Christian; Leyffer, Sven: TACO: a toolkit for AMPL control optimization (2013)
  7. Pintér, János D.; Kampas, Frank J.: Benchmarking nonlinear optimization software in technical computing environments (2013)
  8. Wen, Zaiwen; Yin, Wotao: A feasible method for optimization with orthogonality constraints (2013)
  9. Gratton, Serge; Mouffe, Mélodie; Toint, Philippe L.: Stopping rules and backward error analysis for bound-constrained optimization (2011)
  10. Moré, Jorge J.; Wild, Stefan M.: Estimating computational noise (2011)
  11. Fourer, Robert; Orban, Dominique: DrAmpl: A meta solver for optimization problem analysis (2010)
  12. Neun, Winfried; Sturm, Thomas; Vigerske, Stefan: Supporting global numerical optimization of rational functions by generic symbolic convexity tests (2010)
  13. Shen, Chungen; Xue, Wenjuan; Pu, Dingguo: An infeasible nonmonotone SSLE algorithm for nonlinear programming (2010)
  14. Armand, Paul; Benoist, Joël; Orban, Dominique: Dynamic updates of the barrier parameter in primal-dual methods for nonlinear programming (2008)
  15. Morales, José Luis; Nocedal, Jorge; Smelyanskiy, Mikhail: An algorithm for the fast solution of symmetric linear complementarity problems (2008)
  16. Audet, Charles; Hansen, Pierre; Messine, Frédéric: Extremal problems for convex polygons (2007)
  17. Munson, Todd: Mesh shape-quality optimization using the inverse mean-ratio metric (2007)
  18. Addis, Bernardetta; Leyffer, Sven: A trust-region algorithm for global optimization (2006)
  19. Neumaier, Arnold; Shcherbina, Oleg; Huyer, Waltraud; Vinkó, Tamás: A comparison of complete global optimization solvers (2005)
  20. Spellucci, P.: Nonlinear (local) optimization. The state of the art (2001)