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