This work aims to establish an algorithm for solving the problem of convex programming with several objective-functions with linear constraints. Starting from the idea of Rosen's algorithm for solving the problem of convex programming with linear con-straints and taking into account the solution concept from multi-dimensional programming represented by a program which reaches "the best compromise" we are extending this method in the case of multidimensional programming. The concept of direction of min-imization is introduced and a necessary and sufficient condition is given for a s∈Rn direction to be a direction is min-imal. The two numerical examples presented at the end validate the algorithm.