A 3SDP relaxation to solve vertex cover problem

Vertex cover problem is a famous combinatorial problem, which its complexity has been heavily studied. It is known that it is hard to approximate to within any constant factor better than 2. In this paper, based on the addition of new constraints to the combination of 3 semidefinite programming (SDP) relaxations, we introduce a new stronger SDP relaxation for vertex cover problem which solve it exactly on general graphs. In this manner and by solving one of the NP-complete problems in polynomial time, we conclude that P=NP.This paper, which I have submitted to ACM Transactions on algorithms, is an extended SDP relaxation model of a well known SDP model (Karakostas SDP model : 2005) accompanying with 3 Theorems. Indeed, by coping the constraints of 3 such SDP model proposed by Karakostas et al. (2005), and addition of 3 set of constraints to it (the 3 vectors Vo and the 3 vectors Vi must have angles 120 to each other which caused they are Co-plannar) I proved that the inner multiplication of optimal vectors are equals to -1, 0, or 1, and therefore the proposed model can solve the vertex cover problem, exactly