This paper proposes a filter method for solving nonlinear semidefinite programming problems. Our method extends to this setting the filter SQP (sequential quadratic programming) algorithm, recently introduced for solving nonlinear programming problems, obtaining the respective global convergence results. Mathematical subject classification: 90C30, 90C55.

Software development project employs some Quality Control (QC) process to detect and remove defects. The final quality of the delivered software depends on the effort spent on all the QC stages. Given a quality goal, different combinations of efforts for the different QC stages may lead to the same goal. In this paper we address the problem of allocating resources to the different QC stages, su...

This paper describes a software package for the solution of Nonlinear Programming (NLP) problems. The package implements a Sequential Quadratic Programming solver with a “filter” to promote global convergence. The solver runs with a dense or a sparse linear algebra package and a robust QP solver.

This paper describes a software package for the solution of Nonlinear Programming (NLP) problems. The package implements a Sequential Quadratic Programming solver with a \\lter" to promote global convergence. The solver runs with a dense or a sparse linear algebra package and a robust QP solver.

Sequential Quadratic Programming (SQP) for trajectory optimization of entry vehicle was presented. Firstly, equations of motion were normalized and an independent variable is introduced to reduce the difficulty of iterative computation. And then, optimal control problem was transformed into a nonlinear programming problem using direct collocation method. Finally, sequential quadratic programmin...

The relationship between the mathematical program with linear complementarity constraints (MPCC) and its inequality relaxation is studied. A new sequential quadratic programming (SQP) method is presented for solving the MPCC based on this relationship. A certain SQP technique is introduced to deal with the possible infeasibility of quadratic programming subproblems. Global convergence results a...

in this paper, we deal to obtain some new complexity results for solving semidefinite optimization (sdo) problem by interior-point methods (ipms). we define a new proximity function for the sdo by a new kernel function. furthermore we formulate an algorithm for a primal dual interior-point method (ipm) for the sdo by using the proximity function and give its complexity analysis, and then we sho...