"kumar vishwajeet" wrote in message <email@example.com>... > Hi, > I have an objective function of the following type: > J = x log(x/k) + cx > Subject to : f1(x) = alpha and f2(x) = beta > where alpha, beta, k and c are constants and x is a vector to be solved for. So, it is a convex function. Which is the best optimization routine in MATLAB to solve such problems. I'm currently using fmincon and it is slower than snail. ==========
Is c a vector? I.e., is cx the same as dot(c,x)?
Also you haven't said what f1(x) and f2(x) look like. Unless they are linear, the problem is not a convex program overall.
One reason things might be slow is x log(x/k) is not differentiable at x=0, which violates the rules of fmincon if x=0 is in the feasible set. Do you also have a constraint x>=epsilon>0?