An SQP Algorithm for Optimization with Linear Complementary Constraints.

Against the shortcomings that many existing algorithms for solving the standard smoothing nonlinear programming (SSNP) would fail if they were used directly to solve the mathematical programs with equilibrium constraints (MPEC). By using a complementarity function and the idea of smoothing approximation method, the MPEC problem was transformed into a nonlinear programming, and an SQP algorithm is proposed for the solution of MPEC problem. Further the numerical solution to the algorithm is given. Preliminary numerical results show that it can be a very good convergence speed and optimization results. [ABSTRACT FROM AUTHOR]