init

FOTF Toolbox/fminsearchbnd/test/test_main.m

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+%% Optimization of a simple (Rosenbrock) function, with no constraints
+% The unconstrained solution is at [1,1]
+rosen = @(x) (1-x(1)).^2 + 105*(x(2)-x(1).^2).^2;
+
+% With no constraints, operation simply passes through
+% directly to fminsearch. The solution should be [1 1]
+xsol = fminsearchbnd(rosen,[3 3])
+
+%% Full lower and upper bound constraints which will all be inactive
+xsol = fminsearchbnd(rosen,[3 3],[-1 -1],[4 4])
+
+%% Only lower bound constraints
+xsol = fminsearchbnd(rosen,[3 3],[2 2])
+
+%% Only upper bound constraints
+xsol = fminsearchbnd(rosen,[-5 -5],[],[0 0])
+
+%% Dual constraints
+xsol = fminsearchbnd(rosen,[2.5 2.5],[2 2],[3 3])
+
+%% Dual constraints, with an infeasible starting guess
+xsol = fminsearchbnd(rosen,[0 0],[2 2],[3 3])
+
+%% Mixed constraints
+xsol = fminsearchbnd(rosen,[0 0],[2 -inf],[inf 3])
+
+%% Provide your own fminsearch options
+opts = optimset('fminsearch');
+opts.Display = 'iter';
+opts.TolX = 1.e-12;
+
+n = [10,5];
+H = randn(n);
+H=H'*H;
+Quadraticfun = @(x) x*H*x';
+
+% Global minimizer is at [0 0 0 0 0].
+% Set all lower bound constraints, all of which will
+% be active in this test.
+LB = [.5 .5 .5 .5 .5];
+xsol = fminsearchbnd(Quadraticfun,[1 2 3 4 5],LB,[],opts)
+
+%% Exactly fix one variable, constrain some others, and set a tolerance
+opts = optimset('fminsearch');
+opts.TolFun = 1.e-12;
+
+LB = [-inf 2 1 -10];
+UB = [ inf  inf 1  inf];
+xsol = fminsearchbnd(@(x) norm(x),[1 3 1 1],LB,UB,opts)
+
+%% All the standard outputs from fminsearch are still returned
+[xsol,fval,exitflag,output] = fminsearchbnd(@(x) norm(x),[1 3 1 1],LB,UB)
+