# Quadratic programming with simplex constraints

I have this quadratic function $x'Ax$ which is not convex. I want to maximize this function subject to the constraints that the solution x lies in a simplex such that $\sum_{i=1}^{n}x_i=1$. That means the solution lies in a simplex and $x \epsilon [0,1]^n$.

I want to write an iterative procedure to do this. Suggestions?

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Do you mean the objective is not concave? That's the kind of objective you want when you're maximizing. If so, I think this will be tricky. Any iterative procedure is likely to find a local maximum, not a global maximum. –  Mike Spivey Dec 7 '12 at 18:46
yeah concave, I mean it's not concave. How should I proceed? –  user34790 Dec 7 '12 at 19:24