A Penalty-Free Method with Trust Region for Nonlinear Semidefinite Programming

作者：Chen Zhongwen^*; Miao Shicai

来源：Asia Pacific Journal of Operational Research, 2015, 32(1): 1540006.

DOI：10.1142/S0217595915400060

• Nonlinear semidefinite programming
• penalty-free method
• measure of constraint violation
• global convergence

In this paper, we propose a class of new penalty-free method, which does not use any penalty function or a filter, to solve nonlinear semidefinite programming (NSDP). So the choice of the penalty parameter and the storage of filter set are avoided. The new method adopts trust region framework to compute a trial step. The trial step is then either accepted or rejected based on the some acceptable criteria which depends on reductions attained in the nonlinear objective function and in the measure of constraint infeasibility. Under the suitable assumptions, we prove that the algorithm is well defined and globally convergent. Finally, the preliminary numerical results are reported.

• 出版日期2015-2
• 单位苏州大学