Finding Global Minima with a Computable Quasi-filled Function for Constrained Global Optimization

Abstract

A novel quasi-filled function approach is proposed in this paper for a constrained global minimization problem. Firstly, the definition of quasi-filled function is given, a quasi-filled function is constructed, and then a quasi-filled function algorithm is proposed. The constructed function contains two parameters and they can be easily adjusted during implementation of the quasi-filled function algorithm. And at last, a numerical test is made. The preliminary computational results demonstrate the efficiency of the proposed quasi-filled function approach.