A new class of filled functions for global minimization

Authors:
Xiaoliang He;Chengxian Xu;Chuanchao Zhu
Affiliations:
School of Science, Xi’an Jiaotong University, Xi’an, China;School of Science, Xi’an Jiaotong University, Xi’an, China;School of Science, Xi’an Jiaotong University, Xi’an, China
Venue:
CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part I
Year:
2005

Citing 7
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Abstract

Filled function method is a type of efficient methods to solve global optimization problems arisen in non-convex programming. In this paper, a new class of filled functions is proposed. This class of filled functions has only one adjustable parameter a. Several examples of this class of filled functions with specified parameter values are given, which contain the filled functions proposed in [3] and [4]. These examples show this class of filled functions contains more simple functions, therefore this class of filled functions have better computability. An algorithm employing the proposed filled function is presented, and numerical experiments show that the proposed filled functions are efficient.