NEWUOA is a software developped by M.J.D. Powell for unconstrained optimization without derivatives. The NEWUOA seeks the least value of a function F(x) (x is a vector of dimension n ) when F(x) can be calculated for any vector of variables x . The algorithm is iterative, a quadratic model being required at the beginning of each iteration, which is used in a trust region procedure for adjusting the variables. When the quadratic model is revised, the new model interpolates F at m points, the value m=2n+1 being recommended.

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  1. Astete-Morales, Sandra; Cauwet, Marie-Liesse; Liu, Jialin; Teytaud, Olivier: Simple and cumulative regret for continuous noisy optimization (2016)
  2. Stich, S.U.; Müller, C.L.; Gärtner, B.: Variable metric random pursuit (2016)
  3. Tröltzsch, Anke: A sequential quadratic programming algorithm for equality-constrained optimization without derivatives (2016)
  4. Wang, Jueyu; Zhu, Detong: Conjugate gradient path method without line search technique for derivative-free unconstrained optimization (2016)
  5. Arouxét, Ma.Belén; Echebest, Nélida E.; Pilotta, Elvio A.: Inexact restoration method for nonlinear optimization without derivatives (2015)
  6. Ferreira, Priscila S.; Karas, Elizabeth W.; Sachine, Mael: A globally convergent trust-region algorithm for unconstrained derivative-free optimization (2015)
  7. Gould, Nicholas I.M.; Orban, Dominique; Toint, Philippe L.: CUTEst: a constrained and unconstrained testing environment with safe threads for mathematical optimization (2015)
  8. Grippo, L.; Rinaldi, F.: A class of derivative-free nonmonotone optimization algorithms employing coordinate rotations and gradient approximations (2015)
  9. Hu, Tao; Qiu, Yan Ping; Cui, Heng Jian; Chen, Li Hong: Numerical discretization-based kernel type estimation methods for ordinary differential equation models (2015)
  10. Krejić, Nataša; Lužanin, Zorana; Nikolovski, Filip; Stojkovska, Irena: A nonmonotone line search method for noisy minimization (2015)
  11. Powell, M.J.D.: On fast trust region methods for quadratic models with linear constraints (2015)
  12. Sampaio, Ph.R.; Toint, Ph.L.: A derivative-free trust-funnel method for equality-constrained nonlinear optimization (2015)
  13. Yuan, Ya-xiang: Recent advances in trust region algorithms (2015)
  14. Breitmoser, Yves; Tan, Jonathan H.W.; Zizzo, Daniel John: On the beliefs off the path: equilibrium refinement due to quantal response and level-$k$ (2014)
  15. Gumma, E.A.E.; Hashim, M.H.A.; Ali, M.Montaz: A derivative-free algorithm for linearly constrained optimization problems (2014)
  16. Sinha, Ankur; Korhonen, Pekka; Wallenius, Jyrki; Deb, Kalyanmoy: An interactive evolutionary multi-objective optimization algorithm with a limited number of decision maker calls (2014)
  17. Zhang, Zaikun: Sobolev seminorm of quadratic functions with applications to derivative-free optimization (2014)
  18. Conejo, P.D.; Karas, E.W.; Pedroso, L.G.; Ribeiro, A.A.; Sachine, M.: Global convergence of trust-region algorithms for convex constrained minimization without derivatives (2013)
  19. Corsini, M.; Dellepiane, M.; Ganovelli, F.; Gherardi, R.; Fusiello, A.; Scopigno, R.: Fully automatic registration of image sets on approximate geometry (2013)
  20. Leskinen, Jyri; Périaux, Jacques: Distributed evolutionary optimization using Nash games and GPUs -- applications to CFD design problems (2013)

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