Proceedings of the 2015 International Conference on Artificial Intelligence and Industrial Engineering

A global Optimization Approach to Non-Convex Problems

Authors
Z.F. Lu, Y. Lan
Corresponding Author
Z.F. Lu
Available Online July 2015.
DOI
10.2991/aiie-15.2015.122How to use a DOI?
Keywords
global optimization; non-convex function; generalized gradient; evolution equation
Abstract

In this paper, a novel approach to find the global optimal solution of the special non-convex problems is proposed. The non-convex objective function is first decomposed into two convex sub-functions. Then a generalized gradient is introduced to determine a search direction and the evolution equation is built to obtain a global minimum point. By the approach, we can prevent the search process from some local minima and search a global minimum point. Two numerical examples are given to prove the approach to be effective.

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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Volume Title
Proceedings of the 2015 International Conference on Artificial Intelligence and Industrial Engineering
Series
Advances in Intelligent Systems Research
Publication Date
July 2015
ISBN
978-94-62520-70-7
ISSN
1951-6851
DOI
10.2991/aiie-15.2015.122How to use a DOI?
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/).

Cite this article

TY  - CONF
AU  - Z.F. Lu
AU  - Y. Lan
PY  - 2015/07
DA  - 2015/07
TI  - A global Optimization Approach to Non-Convex Problems
BT  - Proceedings of the 2015 International Conference on Artificial Intelligence and Industrial Engineering
PB  - Atlantis Press
SP  - 449
EP  - 452
SN  - 1951-6851
UR  - https://doi.org/10.2991/aiie-15.2015.122
DO  - 10.2991/aiie-15.2015.122
ID  - Lu2015/07
ER  -