Constrained Global Optimization Using a New Exact Penalty Function

The aim of this paper is to propose a global algorithm model for continuous constrained nonlinear programming based on a new simple and exact penalty function. Under weak assumptions, we show that the optimizer obtained by the algorithm is converged to the global minimizer of the original problem.