www.gusucode.com > optim 案例源码 matlab代码程序 > optim/LinearInequalityConstraintExample.m
%% Linear Inequality Constraint % Find the minimum value of Rosenbrock's function when there is a linear % inequality constraint. % Copyright 2015 The MathWorks, Inc. %% % Set the objective function |fun| to be Rosenbrock's function. Rosenbrock's % function is well-known to be difficult to minimize. It has its minimum % objective value of 0 at the point (1,1). For more information, see <docid:optim_ug.brg0p3g-1>. fun = @(x)100*(x(2)-x(1)^2)^2 + (1-x(1))^2; %% % Find the minimum value starting from the point |[-1,2]|, constrained to % have $x(1) + 2x(2) \le 1$. Express this constraint in the % form |Ax <= b| by taking |A = [1,2]| and |b = 1|. Notice that this % constraint means that the solution will not be at the unconstrained % solution (1,1), because at that point $x(1) + 2x(2) = 3 > 1$. x0 = [-1,2]; A = [1,2]; b = 1; x = fmincon(fun,x0,A,b)