Smoothing of the lower-order exact penalty function for inequality constrained optimization

Smoothed Lower Order Penalty Function for Constrained Optimization Problems

The paper introduces a smoothing method to the lower order penalty function for constrained optimization problems. It is shown that, under some mild conditions, an optimal solution of the smoothed penalty problem is an approximate optimal solution of the original problem. Based on the smoothed penalty function, an algorithm is presented and its convergence is proved under some mild assumptions....

A second-order differentiable smoothing approximation lower order exact penalty function

In this paper, we give a smoothing approximation to the lower order exact penalty functions for inequality-constrained optimization problems. Error estimations are obtained among the optimal objective function values of the smoothed penalty problem, of the nonsmooth penalty problem and of the original optimization problem. An algorithm based on the smoothed penalty function is presented, which ...

A New Exact Penalty Function Method for Continuous Inequality Constrained Optimization Problems∗

In this paper, a computational approach based on a new exact penalty function method is devised for solving a class of continuous inequality constrained optimization problems. The continuous inequality constraints are first approximated by smooth function in integral form. Then, we construct a new exact penalty function, where the summation of all these approximate smooth functions in integral ...

A Derivative-Free Algorithm for Inequality Constrained Nonlinear Programming via Smoothing of an linfty Penalty Function

In this paper we consider inequality constrained nonlinear optimization problems where the first order derivatives of the objective function and the constraints cannot be used. Our starting point is the possibility to transform the original constrained problem into an unconstrained or linearly constrained minimization of a nonsmooth exact penalty function. This approach shows two main difficult...

Constrained Evolutionary Optimization - the penalty function approach