论文信息 - An improved strongly sub-feasible SSLE method for optimization problems and numerical experiments

An improved strongly sub-feasible SSLE method for optimization problems and numerical experiments

In this paper, the super-linearly and quadratically convergent strong sub-feasible method [J.L. Li, J.B. Jian, A superlinearly and quadratically convergent strongly subfeasible method for nonlinear inequality constrained optimization, OR Transactions, 7 (2) (2003) 21–34] for nonlinear inequality constrained optimization is improved, such that the iterative points can get into the feasible region after a finite number of iterations. As a result, a strict restricted condition can be overcome. Another two contributions of this paper are that a new bidirectional Armijo line search is presented and a lot of numerical comparison results are reported.

[1] E. Panier,et al. A QP-Free, globally convergent, locally superlinearly convergent algorithm for inequality constrained optimization , 1988 .

[2] Klaus Schittkowski,et al. More test examples for nonlinear programming codes , 1981 .

[3] N. Maratos,et al. Exact penalty function algorithms for finite dimensional and control optimization problems , 1978 .

[4] Jian Jin. TWO EXTENSION MODELS OF SQP AND SSLE ALGORITHMS FOR OPTIMIZATION AND THEIR SUPERLINEAR AND QUADRATIC CONVERGENCE , 2001 .

[5] Nicholas I. M. Gould,et al. CUTE: constrained and unconstrained testing environment , 1995, TOMS.

[6] Ya-Xiang Yuan,et al. Optimization theory and methods , 2006 .

[7] S. Lucidi,et al. Quadratically and superlinearly convergent algorithms for the solution of inequality constrained minimization problems , 1995 .

[8] E. Panier,et al. A superlinearly convergent feasible method for the solution of inequality constrained optimization problems , 1987 .

[9] M. J. D. Powell,et al. A fast algorithm for nonlinearly constrained optimization calculations , 1978 .