% MATH 4/5794: Optimization Modeling

% EXAMPLES: W. A. Lodwick - Example 1, Multiple Sclerosis Scab Detection 1

% Example 2, Multiple Sclerosis Scab Detection 2

% Example 3, Multiple Sclerosis Scab Detection 3

% Example 4, Multiple Sclerosis Scab Detection 4

% Example 5, Radiation Therapy (inactive)

% Example 6, Fuzzy Linear Programming (inactive)

% Example 7, Possibilistic Probramming (inactive)

% Example 5, Stochastic Progra8ming (inactive)

% Created: January 20, 2005

%

function [x,z,c] = classdemo2(exnum)

% options=optimset('Gradobj','on');

% x(1): Echo time

% x(2): Pulse repetition time

x0(1,1) = 0;

x0(2,1) = 0;

vlb(1,1) = 10.00000001;

vlb(2,1) = 100;

vub(1,1) = 200;

vub(2,1) = 3000;

% Call the nlp solver

options = optimset('LargeScale','off','MaxIter',200,'Display','iter',...

'MaxFunEvals',2000);

[x,z] =fmincon('introwalobj',x0,[],[],[],[],vlb,vub,'introwalcon', ...

options,exnum);

'The solution is: '

x

% Objective function value - since minimizing to obtain maximum, need negative to

% get the correct maximum

z = -z;

'Objective function value is: '

z

% Constraints - how close the solution is to satisfying the constraints

[c,ceq] = introwalcon(x,exnum);

'Constraints are'

c = -c;

c