Hy, I have to solve the following minimization problem on x Q(x) = 1/2 x' A x + x'b where Q is a quadratic form and x is in the simplex (x_i>=0, sum_i x_i = 1, i=1,...,n), A pos. def. and b a negative vector. I have tried with quadprog routines but it gives me solutions of the form x* = (...,1,..) where the dots "." are zeroes "0". the toolbox optim/quadprog in Matlab lead to the same results as R+quaprog package (they use the "same" qld algorithm). Are there any more efficient methods based on lagrange multipliers + standard simplex minimization ? I think that the qld algorithm is rather general and then not efficient for my specific case. Any idea or reference ? Stefano -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-devel mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-devel-request@stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._