Code covered by the BSD License
-
evallag (f, c, x, lambda)
Evaluate the lagrangian system and it's first derivative in a pair
-
evbranin(x)
Name: Branin
-
evbrown(x)
Name: Brown's Almost Linear
-
evbullardbiegler(x)
Name: Bullard&Biegler
-
evcg11(x)
-
evcg13(x)
-
evcg3(x)
-
evcombustion(x)
Name: Equilibrium Combustion
-
eveasom(x)
Name: Easom
-
evferraristronconi(x)
Name: Ferraris&Tronconi
-
evfg11(x)
-
evfg13(x)
-
evfg3(x)
-
evgoldsteinprice(x)
Name: Goldstein&Price
-
evgriewank(x)
Name: Griewank
-
evhimmelblau(x)
Name: Himmelblau
-
evhumpcamel(x)
Name: Three Hump Camel
-
evkubicek(x)
Name: Kubicek
-
evlevy(x)
Name: Levy
-
evmichalewicz(x)
Name: Michalewicz
-
evrastrigin(x)
Name: Rastrigin
-
evrosenbrock(x)
Name: Rosenbrock
-
evshubert(x)
Name: Shubert
-
evsmith(x)
Name: Smith
-
evtrigonometric(x)
Name: Trigonometric
-
intdiv(a, b)
Extended interval division. This implementation follows the technical
-
intksolve(f, x0, options)
Apply the Krawczyk operator to test existence of zeros of a nonlinear
-
intmincon(f, x0, nonlcon, opt...
Find the global minima of a function f inside a box x0 subject to
-
intminunc(f, x0, options)
Find the global minima of a function f inside the box x0. The user must
-
intoptimget(options)
Display parameters setted by an option vector. If no input arguments are
-
intoptimset()
Create an optimization options vector. To change default settings on
-
intsolve(f, x0, options)
Find all zeros of a nonlinear system of equations inside an
-
nonnullgs (X, x, b, M)
Perform one step of the interval gauss seidel method to solve the problem
-
nullgs (X, x, b, M)
Perform one step of the interval gauss seidel method to solve the problem
-
sibranin(type)
Branin problem initial data.
-
sibrown(type)
Brown Almost linear problem initial data.
-
sibullardbiegler(type)
Bullard&Biegler problem initial data.
-
sicombustion(type)
Combustion problem initial data.
-
sieasom(type)
Rastrigin problem initial data.
-
siferraristronconi(type)
Ferraris&Tronconi problem initial data.
-
sig11(type)
-
sig13(type)
-
sig3(type, n)
-
sigoldsteinprice(type)
Goldstein&Price problem initial data.
-
sigriewank(type, n)
Griewank's problem initial data.
-
sihimmelblau(type)
Himmelblau problem initial data.
-
sihumpcamel(type)
Three hump camel problem initial data.
-
sikubicek(type)
Kubicek problem initial data.
-
silevy(type, n)
Levy's problem initial data.
-
simichalewicz(type, n)
Michalewicz's problem initial data.
-
sirastrigin(type, n)
Rastrigin problem initial data.
-
sirosenbrock(type, n)
Ronsenbrock's problem initial data.
-
sishubert(type)
Shubert's problem initial data.
-
sismith(type)
Smith problem initial data.
-
sitrigonometric(type, n)
Trigonometric problem initial data.
-
View all files
from
INTSOLVER: An interval based solver for Global Optimization
by Tiago Montanher
Interval based functions to solve small global optimization problems with guaranteed bounds.
|
| eveasom(x) |
function y = eveasom(x)
% Name: Easom
% Variables: 2
% Initial Point/ Initial Interval: (1,...,1) / ([-15, 30],...,[-15, 30])
% Reported Solution: (0,...,0)
% Minima: 0
% Matlab Code by A. Hedar (Nov. 23, 2005).
y = -cos(x(1))*cos(x(2))*exp(-(x(1)-pi)^2-(x(2)-pi)^2);
end
|
|
Contact us at files@mathworks.com
