TEST_OPT_CON
Test Functions for Scalar Optimization
Constrained to a HyperRectangle
TEST_OPT_CON
is a MATLAB library which
defines a set of constrained global optimization problems.
A typical constrained global optimization problem presents an Mdimensional
hyperrectangle bounded by A(1:M) <= X(1:M) <= B(1:M), and a scalarvalued
function F(X). The task is to find a point X within the hyperrectangle
at which the function takes its minimum value.
This task is impossible, mathematically and in general. However, the problems
that can be solved mathematically are often not the ones encountered in
real life. Thus, it is useful to try to solve an impossible problem, since
an approximate answer to such a problem can be all we can hope for or need.
The functions defined include:

NM1: NiederreiterMcCurley function #1, M = 4;

NM2: NiederreiterMcCurley function #2, M = 4;

NM3: NiederreiterMcCurley function #3, M = 4;

NM4: NiederreiterMcCurley function #4, M = 4;

NM5: NiederreiterMcCurley function #5, M = 4;

NM6: NiederreiterMcCurley function #6, M = 4;

L02: Langerman function, M = 2;

L10: Langerman function, M = 10;
For each function, the library includes a routine to evaluate the function,
but also routines to return the limits of the hyperrectangle, the
spatial dimension, the solution, if known, and a title for the problem.
These routines have a standard set of names based on the function index.
For instance, for function #3, we have the routines:

P03_AB returns bounds for problem 3.

P03_F returns the objective function value for problem 3.

P03_M returns the spatial dimension for problem 3.

P03_SOL returns known solutions for problem 3.

P03_TITLE returns a title for problem 3.
Since the same interface is used for each function,
if you wish to work with problem 6 instead, you simply change
the "03" to "06" in your routine calls.
If you wish to call all of the functions, you can write a concise
program to do so by using the generic interface, in which the function
names use the prefix P00_, and require the specific problem index
to be supplied as an extra input argument:

P00_AB returns bounds for a problem specified by index.

P00_F returns the objective function value for a problem specified by index.

P00_M returns the spatial dimension for a problem specified by index.

P00_SOL returns known solutions for a problem specified by index.

P00_TITLE returns a title for a problem specified by index.
Licensing:
The computer code and data files described and made available on this
web page are distributed under
the GNU LGPL license.
Languages:
TEST_OPT_CON is available in
a C version and
a C++ version and
a FORTRAN77 version and
a FORTRAN90 version and
a MATLAB version.
Related Data and Programs:
ASA047,
a MATLAB library which
minimizes a scalar function of several variables using the NelderMead algorithm.
BRENT,
a MATLAB library which
contains Richard Brent's routines for finding the zero, local minimizer,
or global minimizer of a scalar function of a scalar argument, without
the use of derivative information.
COMPASS_SEARCH
a MATLAB program which
minimizes a scalar function of several variables using the compass search algorithm.
ENTRUST,
a MATLAB program which
minimizes a scalar function of several variables using trustregion methods.
FMINCON,
a MATLAB library which
demonstrates the use of the fmincon() function to seek the minimizer
of a function f(x) subject to a constraint.
NELDER_MEAD,
a MATLAB program which
minimizes a scalar function of several variables using the NelderMead
algorithm, by Jeff Borggaard.
POLYNOMIALS,
a MATLAB library which
defines multivariate polynomials over rectangular domains, for
which certain information is to be determined, such as the maximum
and minimum values.
PRAXIS,
a MATLAB library which
minimizes a scalar function of several variables, without
requiring derivative information,
by Richard Brent.
TEST_OPT,
a MATLAB library which
defines test problems
requiring the minimization of a scalar function of several variables.
TEST_OPTIMIZATION,
a MATLAB library which
defines test problems for the minimization of a scalar function
of several variables, as described by Molga and Smutnicki.
TOMS178,
a MATLAB library which
optimizes a scalar functional of multiple variables using the
HookeJeeves method.
Reference:

Harald Niederreiter, Kevin McCurley,
Optimization of functions by quasirandom search methods,
Computing,
Volume 22, Number 2, 1979, pages 119123.
Source Code:

p00_ab.m,
returns bounds for a problem specified by index.

p00_f.m,
returns the objective function value for a problem specified by index.

p00_m.m,
returns the spatial dimension for a problem specified by index.

p00_problem_num.m,
returns the number of problems.

p00_sol.m,
returns known solutions for a problem specified by index.

p00_title.m,
returns a title for a problem specified by index.

p01_ab.m,
returns bounds for problem 1.

p01_f.m,
returns the objective function value for problem 1.

p01_m.m,
returns the spatial dimension for problem 1.

p01_sol.m,
returns known solutions for problem 1.

p01_title.m,
returns a title for problem 1.

p02_ab.m,
returns bounds for problem 2.

p02_f.m,
returns the objective function value for problem 2.

p02_m.m,
returns the spatial dimension for problem 2.

p02_sol.m,
returns known solutions for problem 2.

p02_title.m,
returns a title for problem 2.

p03_ab.m,
returns bounds for problem 3.

p03_f.m,
returns the objective function value for problem 3.

p03_m.m,
returns the spatial dimension for problem 3.

p03_sol.m,
returns known solutions for problem 3.

p03_title.m,
returns a title for problem 3.

p04_ab.m,
returns bounds for problem 4.

p04_f.m,
returns the objective function value for problem 4.

p04_m.m,
returns the spatial dimension for problem 4.

p04_sol.m,
returns known solutions for problem 4.

p04_title.m,
returns a title for problem 4.

p05_ab.m,
returns bounds for problem 5.

p05_f.m,
returns the objective function value for problem 5.

p05_m.m,
returns the spatial dimension for problem 5.

p05_sol.m,
returns known solutions for problem 5.

p05_title.m,
returns a title for problem 5.

p06_ab.m,
returns bounds for problem 6.

p06_f.m,
returns the objective function value for problem 6.

p06_m.m,
returns the spatial dimension for problem 6.

p06_sol.m,
returns known solutions for problem 6.

p06_title.m,
returns a title for problem 6.

p07_ab.m,
returns bounds for problem 7.

p07_f.m,
returns the objective function value for problem 7.

p07_m.m,
returns the spatial dimension for problem 7.

p07_sol.m,
returns known solutions for problem 7.

p07_title.m,
returns a title for problem 7.

p08_ab.m,
returns bounds for problem 8.

p08_f.m,
returns the objective function value for problem 8.

p08_m.m,
returns the spatial dimension for problem 8.

p08_sol.m,
returns known solutions for problem 8.

p08_title.m,
returns a title for problem 8.

r8col_uniform.m,
fills an R8COL with scaled pseudorandom numbers.

timestamp.m,
prints the YMDHMS date as a timestamp.
Examples and Tests:
You can go up one level to
the MATLAB source codes.
Last revised on 16 February 2012.