we present a structured algorithm for solving constrained nonlinear least squares problems, and establish its local two-step q-superlinear convergence. the approach is based on an adaptive structured scheme due to mahdavi-amiri and bartels of the exact penalty method of coleman and conn for nonlinearly constrained optimization problems. the structured adaptation also makes use of the ideas of n...

We address the problem of minimizing a quadratic function subject to linear constraints over binary variables. introduce exact solution method called EXPEDIS where constrained is transformed into max-cut instance, and then thewhole machinery available for can be used solve problem. derive theory in order find transformation spirit an penalty method; however, we are only interested exactness set...

In this paper an exact penalty line search is introduced for solving constrained nonlinear programing. By this method it is possible to solve some problems with combining penalty method and SQP method, and in any iteration for producing new stepone can uses linear search and solves unconstrained optimization by exact penalty function. In this method a linear programming subproblem with trust ar...

We present a general theory of exact penalty functions with vectorial (multidimensional) parameter for optimization problems in infinite dimensional spaces. In comparison the scalar case, use parameters provides much more flexibility, allows one to adaptively and independently take into account violation each constraint during an process, often leads better overall performance method using func...