Hello I am using the simplex minimisation to solve a problem of crystallography. The function to minimize is : f = f(euler_x, euler_y, euler_z, a, b, c, alpha, beta, gamma);
in fact a, b, c, alpha, beta, gamma are the parameters of a triedra, a, b, c, are the length of the sides and alpha, beta, gamma the angles of the triedra. for some combinations of alpha, beta, gamma , f(blabla...) = GSL_NAN. So the simplex can not converge. If I return a really big number as it was suggested in a previous thread of the mailing list, the simplex must be contracted around the better corner. But it is not always possible to obtain a valid contraction in one guess. To be clear this simplex algorithm only work for a convex space. And my problem is not convex. Nevertheless if we are close enough of the solution, the problem become locally convex. To achieve this, we must contraction the simplex till it becomes valid. Is it possible to tune the simplex algorithm to solve also those locally convex problems. Another problem is that the initial guest of the simplex is not always possible. Can I create by myself the starting points of the simplex ? Frederic
