Proceedings of the 2nd Annual International Conference on Advanced Material Engineering (AME 2016)

Multi-modal Function Optimization of Immune Clone Based on Uniform Design

Authors
Bo Hu
Corresponding Author
Bo Hu
Available Online June 2016.
DOI
10.2991/ame-16.2016.219How to use a DOI?
Keywords
Immune Optimization, Multimodal Function, Population Distribution, Local Search, Uniform Design.
Abstract

In order to obtain all the optimal solutions of multimodal functions as much as possible, a multi peak function optimization based on uniform design is proposed. The algorithm adopts uniform design to initialize the population and ensure the uniformity and diversity of the initial antibody population distribution. Larmark learning strategy is used to search the local population in order to enhance the convergence speed and precision of the algorithm. In the immune clonal parameter setting, the parameter setting problem is described as a multi factor and multi level uniform design problem. Experimental results show that the algorithm is better in finding the best.

Copyright
© 2016, 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/).

Download article (PDF)

Volume Title
Proceedings of the 2nd Annual International Conference on Advanced Material Engineering (AME 2016)
Series
Advances in Engineering Research
Publication Date
June 2016
ISBN
978-94-6252-208-4
ISSN
2352-5401
DOI
10.2991/ame-16.2016.219How to use a DOI?
Copyright
© 2016, 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  - Bo Hu
PY  - 2016/06
DA  - 2016/06
TI  - Multi-modal Function Optimization of Immune Clone Based on Uniform Design
BT  - Proceedings of the 2nd Annual International Conference on Advanced Material Engineering (AME 2016)
PB  - Atlantis Press
SP  - 1349
EP  - 1353
SN  - 2352-5401
UR  - https://doi.org/10.2991/ame-16.2016.219
DO  - 10.2991/ame-16.2016.219
ID  - Hu2016/06
ER  -