THE SEQUENTIAL QUADRATIC PROGRAMMING FOR SYMMETRIC PARETO EIGENVALUE COMPLEMENTARITY PROBLEM

In this article, a sequential quadratic programming (SQP) algorithm framework is proposed to solve the symmetric Pareto Eigenvalue Complementarity Problem (EiCP). In the algorithm framework, the search direction can be constructed by solving a quadratic programming subproblem in each iteration, and the precise step size can be obtained to ensure the reduction of the penalty function. Moreover, the global convergence of this algorithm is discussed. In order to improve the computational efficiency, a simple SQP algorithm is recommended to the large symmetric Pareto EiCP. Various numerical results of the symmetric Pareto EiCPs are reported to illustrate the efficiency of the proposed algorithms.