A sequential quadratic programming (SQP) method is proposed to solve the distributed beamforming problem in multiple relay networks. The problem is formulated as the minimization of the total relay transmit power, subject to individual signal-to-interference-and-noise ratio constraints at each receiver, which is a nonconvex quadratic constraint quadratic programming. Rather than solving its semi-definite programming (SDP) relaxation, we apply the SQP method to solve its tightened form to replace its inequality constraints with equalities. Its global convergence is guaranteed. Simulations show that it not only runs much faster, but also performs as good as SDP for calculation results.