function rod_opt_class

% First solve using fmincon
x0 = 10*ones(2,1);
options = optimset('Display','iter','MaxIter',100,'MaxFunEvals',500,'LargeScale','off');
A = [];
b = [];
Aeq = [];
beq = [];
%lb = 0.1*ones(2,1);
lb = [];
ub = [];

x = fmincon(@cost,x0,A,b,Aeq,beq,lb,ub,@constraints,options)
pause

% Now solve using fminsearch

x = fminsearch(@augcost,x0,options)

function f = cost(x)

x1 = x(1,1);
x2 = x(2,1);

f = 120000/(x1*x2^2);

function [c,ceq] = constraints(x)

x1 = x(1,1);
x2 = x(2,1);

c = [];
ceq = x1^2+x2^2-400;

function f = augcost(x)

x1 = x(1,1);
x2 = x(2,1);

cost = 120000/(x1*x2^2);
penalty = (x1^2+x2^2-400)^2;
w = 10;

f = cost+w*penalty;