A.R. Conn, N. Gould, and Ph.L. Toint. Constrained and unconstrained testing environment. http://www.dci.clrc.ac.uk/Activity.asp?CUTE. Home/Search Document Details and Download
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Interior-Point Methods For Nonconvex Nonlinear Programming.. - David Shanno And (1999) (8 citations) (Correct)
....total number is 2404. While individual problems can vary significantly, overall the predictor corrector method seems to do very well. In addition to the Hock and Schittkowski test sets, we compared the two algorithms on three models from the second author s website [12] and 15 models from the CUTE [3] library of test problems. Some of these problems are larger (and therefore more interesting) As the problems get more difficult, the benefits of using the predictor corrector method become more apparent. The results are contained in the table 2. While this work is still preliminary, and the test ....
A.R. Conn, N. Gould, and Ph.L. Toint. Constrained and unconstrained testing environment. http://www.dci.clrc.ac.uk/Activity.asp?CUTE.
Interior-Point Methods for Nonconvex Nonlinear.. - Benson, Shanno.. (2000) (5 citations) (Correct)
....derivatives, we have chosen to formulate the models in AMPL [6] a modelling language that provides analytic first and second partial derivatives. In order to construct a meaningful test suite, we have been engaged in reformulating from standard input format (SIF) to AMPL all models in the CUTE [2] (constrained and unconstrained testing environment) test suite. To date, we have converted and validated 699 models. For those problems with variable size, we have used the largest reported number of variables and constraints, except in the case of the ncvxqp family of problems and fminsurf, ....
I. Bongartz, A.R. Conn, N. Gould, and Ph.L. Toint. Constrained and unconstrained testing environment. www.cse.clrc.ac.uk/Activity/CUTE+74.
Interior-Point Methods For Nonconvex Nonlinear.. - Benson, Shanno.. (2000) (5 citations) (Correct)
....derivatives, we have chosen to formulate the models in AMPL [8] a modelling language that provides analytic first and second partial derivatives. In order to construct a meaningful test suite, we have been engaged in reformulating from standard input format (SIF) to AMPL all models in the CUTE [4] (constrained and unconstrained testing environment) test suite. To date, we have converted and validated 699 models. For those problems with variable size, we have used the largest reported number of variables and constraints, except in the case of the ncvxqp family of problems and fminsurf, ....
I. Bongartz, A.R. Conn, N. Gould, and Ph.L. Toint. Constrained and unconstrained testing environment. http://www.cse.clrc.ac.uk/Activity/CUTE+74. 14
Case Studies In Trajectory Optimization: Trains, Planes, And.. - Vanderbei (2000) (Correct)
....iterations) More iterations are needed because, as stated earlier, this method suffers more from ringing but even on a per iteration basis the midpoint model solves twice as fast. The trapezoidal discretization of the train model that we ve studied here derives from the model trainh in the CUTE [7] suite on test problems. The CUTE model was itself adapted from a paper by Kautsky and Nichols [13] 8 VANDERBEI param N : 2001; param time : 4.8; param length : 6.0; param ns : 3; param z 1. ns 1 ; param s 1. ns ; param h : time N; param uamax : 10.0; param ubmax : 2.0; param ....
I. Bongartz, A.R. Conn, N. Gould, and Ph.L. Toint. Constrained and unconstrained testing environment. http://www.cse.clrc.ac.uk/Activity/CUTE+74. 7
LOQO: An Interior Point Code For Quadratic Programming - Vanderbei (1998) (77 citations) (Correct)
....normalizer used in the relativization might be of the wrong magnitude. This might have been the case for both forplan and pilotnov since the initial relative infeasibility was in both cases greater that 1.00e 03. Another collection of problems in the repository come from the CUTE set of problems [2]. Results for these problems are shown in Tables 6 and 7. Of the 76 problems in this set, all but 3 were easy to solve to optimality. The 3 that we didn t solve (cvxqp1 l, cvxqp2 l, and cvxqp3 l) were simply too large to solve in a reasonable amount of time on our hardware. LOQO: AN INTERIOR ....
A.R. Conn, N. Gould, and Ph.L. Toint. Constrained and unconstrained testing environment. http://www.dci.clrc.ac.uk/Activity.asp?CUTE.
Nonlinear programming algorithms using trust regions.. - Gomes, Maciel.. (1997) (6 citations) (Correct)
.... Gamma6 ; 10 Gamma6 kx k k1 g or b) kC(x k )k 1 10 Gamma6 and jQ k (0) Gamma Q k (s c ) Gamma Delta T k (A(x k )s c C(x k ) j 10 Gamma8 . 7. 1 Experiments with C 2 problems The first set of test problems (solved using a SUN SPARC station 2 ) was taken from the data base CUTE [2]. A total of 45 constrained optimization problems were selected, where the analytic second derivatives of the functions are available. The selection of problems was made trying to cover from small to relatively large problems, with a wide scope of non linearity. The initial points and initial ....
I. Bongartz, A. R. Conn, N. Gould and Ph. L. Toint, "Constrained and unconstrained testing environment", ACM Transactions on Mathematical Software 21 (1995) 123-160.
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