A Novel Filled Function Approach for Non-Smooth Global Optimization Problem

DOI

10.2991/aiie-15.2015.121How to use a DOI?

Keywords

non-smooth box constrained global optimization; filled function;filled function approach; global minimizer

Abstract

This paper presents a novel filled function approach for a general non-smooth box constrained global optimization problem. The idea of the filled function approach is that by utilizing a transforming function constructed at the given local minimizer of the objective function, the original problem could escape from the current local minimizer and identify an improved one. The proposed filled function contains two parameters, which can be readily adjusted at each iteration. The properties of the filled function are discussed, and a corresponding filled function algorithm is designed. Numerical experiments on several testing problems are implemented, and the preliminary computational results are also reported.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - W.X. Wang
AU  - Y.L. Shang
PY  - 2015/07
DA  - 2015/07
TI  - A Novel Filled Function Approach for Non-Smooth Global Optimization Problem
BT  - Proceedings of the 2015 International Conference on Artificial Intelligence and Industrial Engineering
PB  - Atlantis Press
SP  - 445
EP  - 448
SN  - 1951-6851
UR  - https://doi.org/10.2991/aiie-15.2015.121
DO  - 10.2991/aiie-15.2015.121
ID  - Wang2015/07
ER  -