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if f(x1,x2,..,xn) is convex (or concave) then minimizing or maximizing subject to the linear constraint g(x1,x2,..,xn)=0 should be the same as minimizing or maximizing
F(x1,x2,...,xn,L) = f(x1,x2,...xn) + L*g(x1,x2,...,xn)
in the unconstrained sense. See "minimize?" for help. Convex functions (or concave) functions will have a unique minimum (or unique maximum), so everything should work out.
