07-Jan-2022 23:16:19

nelder_mead_test():
  MATLAB/Octave version 9.8.0.1380330 (R2020a) Update 2
  Test nelder_mead().

NELDER_MEAD_TEST01:
  Use the Himmelblau optimization function.

  Initial data:

  ---X(1)---  ---X(2)---  ---F(X)---

    5.000000   -5.000000  6.100000e+02
    2.000000   -4.000000  2.420000e+02
   -1.000000   -2.000000  1.600000e+02

  Computed optimum after 87 evaluations:

  ---X(1)---  ---X(2)---  ---F(X)---

   -3.779246   -3.283198  2.655792e-07

NELDER_MEAD_TEST02:
  Use the Himmelblau optimization function.

  Initial data:

  ---X(1)---  ---X(2)---  ---F(X)---

    3.000000    4.000000  1.480000e+02
   -2.000000    2.000000  5.000000e+01
    1.000000    1.000000  1.060000e+02

  Computed optimum after 66 evaluations:

  ---X(1)---  ---X(2)---  ---F(X)---

   -2.804998    3.131429  1.038228e-06

NELDER_MEAD_TEST03:
  Use the extended Rosenbrock optimization function.

  Initial data:

  ---X(1)---  ---X(2)---  ---X(3)---  ---X(4)---  ---F(X)---

   -1.000000    0.000000    3.000000    1.000000  6.508000e+03
    2.000000    1.000000   -2.000000    0.000000  2.510000e+03
    0.000000    0.000000    0.000000    0.000000  2.000000e+00
    1.000000    3.000000   -2.000000    1.000000  1.309000e+03
   -1.000000   -1.000000   -1.000000   -1.000000  8.080000e+02

  Computed optimum after 209 evaluations:

  ---X(1)---  ---X(2)---  ---X(3)---  ---X(4)---  ---F(X)---

    1.000167    1.000301    1.000131    1.000227  2.810066e-07

NELDER_MEAD_TEST04:
  Use the Goldstein-Price optimization function.

  Initial data:

  ---X(1)---  ---X(2)---  ---F(X)---

   -4.000000    5.000000  3.444365e+07
    2.000000    3.000000  3.767075e+06
    1.000000   -4.000000  2.644041e+07

  Computed optimum after 79 evaluations:

  ---X(1)---  ---X(2)---  ---F(X)---

    0.000006   -0.999964  3.000001e+00

NELDER_MEAD_TEST05:
  Use the Beale optimization function.

  Initial data:

  ---X(1)---  ---X(2)---  ---F(X)---

    1.000000    4.000000  4.624453e+03
    2.000000    3.000000  3.347203e+03
    1.000000   -4.000000  4.200453e+03

  Computed optimum after 65 evaluations:

  ---X(1)---  ---X(2)---  ---F(X)---

    3.001605    0.500393  4.119185e-07

NELDER_MEAD_TEST06:
  Use the Powell optimization function.

  Initial data:

  ---X(1)---  ---X(2)---  ---X(3)---  ---X(4)---  ---F(X)---

    3.000000   -1.000000    0.000000    1.000000  5.500000e+01
    4.000000   -1.000000    0.000000    1.000000  4.700000e+01
    3.000000    0.000000    0.000000    1.000000  1.400000e+01
    3.000000   -1.000000    1.000000    1.000000  6.200000e+01
    3.000000   -1.000000    0.000000    2.000000  5.500000e+01

  Computed optimum after 174 evaluations:

  ---X(1)---  ---X(2)---  ---X(3)---  ---X(4)---  ---F(X)---

   -0.000730    0.000073    0.000079   -0.000472  3.768369e-07

NELDER_MEAD_TEST07:
  Use the Local optimization function.

  Initial data:

  ---X(1)---  ---X(2)---  ---F(X)---

    1.000000    1.000000  3.330769e+06
    2.000000    1.000000  4.227361e+06
    1.000000    2.000000  1.845619e+07

  Computed optimum after 211 evaluations:

  ---X(1)---  ---X(2)---  ---F(X)---

    0.285630    0.279335  5.922563e+00

NELDER_MEAD_TEST08:
  Use the McKinnon optimization function.

  Initial data:

  ---X(1)---  ---X(2)---  ---F(X)---

    0.000000    0.000000  0.000000e+00
    1.000000    1.000000  8.000000e+00
    0.843070   -0.593070  4.023268e+00

  Computed optimum after 95 evaluations:

  ---X(1)---  ---X(2)---  ---F(X)---

    0.000000    0.000000  0.000000e+00

nelder_mead_test():
  Normal end of execution.

07-Jan-2022 23:16:19