Home   >   CSC-OpenAccess Library   >    Manuscript Information
The Convergence Speed of Single- And Multi-Objective Immune Algorithm Based Optimization Problems
Prof. M. Abo-Zahhad, Sabah M. Ahmed, Nabil Sabor, Ahmad F. Al-Ajlouni
Pages - 247 - 266     |    Revised - 30-11-2010     |    Published - 20-12-2010
Volume - 4   Issue - 5    |    Publication Date - December 2010  Table of Contents
MORE INFORMATION
KEYWORDS
Immune Algorithm, Digital Filters, convergence, Optimization
ABSTRACT
Despite the considerable amount of research related to immune algorithms and its applications in numerical optimization, digital filters design, and data mining, there is still little work related to issues as important as sensitivity analysis, [1]-[4]. Other aspects, such as convergence speed and parameters adaptation, have been practically disregarded in the current specialized literature [7]-[8]. The convergence speed of the immune algorithm heavily depends on its main control parameters: population size, replication rate, mutation rate, clonal rate and hyper-mutation rate. In this paper we investigate the effect of control parameters variation on the convergence speed for single- and multi-objective optimization problems. Three examples are a devoted for this purpose; namely the design of 2-D recursive digital filter, minimization of simple function, and banana function. The effect of each parameter on the convergence speed of the IA is studied considering the other parameters with fix values and taking the average of 100 times independent runs. Then, the concluded rules are applied on some examples introduced in [2] and [3]. Computational results show how to select the immune algorithm parameters to speedup the algorithm convergence and to obtain the optimal solution.
CITED BY (12)  
1 Sabor, N., Abo-Zahhad, M., Sasaki, S., & Ahmed, S. M. (2016). An Unequal Multi-hop Balanced Immune Clustering protocol for wireless sensor networks. Applied Soft Computing, 43, 372-389.
2 Hong, L., & Kamruzzaman, J. A new convergence rate estimation of general artificial immune algorithm. Journal of Intelligent and Fuzzy Systems.
3 Hong Lu, Gong Chenglong, Wang Jingzhuo, & SOUTHERN. (2015). Elite class clonal selection algorithm Mean convergence rate estimate. Journal of Electronics, 43 (5), 916-921.
4 Abo-Zahhad, M., Ahmed, S. M., Sabor, N., & Sasaki, S. (2015). Rearrangement of mobile wireless sensor nodes for coverage maximization based on immune node deployment algorithm. Computers & Electrical Engineering.
5 Abo-Zahhad, M., Ahmed, S. M., Sabor, N., & Al-Ajlouni, A. F. (2015). Wavelet Threshold-Based ECG Data Compression Technique Using Immune Optimization Algorithm. International Journal of Signal Processing, Image Processing and Pattern Recognition, 8(2), 347-360.
6 Abo-Zahhad, M., Ahmed, S. M., Sabor, N., & Sasaki, S. (2014, May). Coverage maximization in mobile Wireless Sensor Networks utilizing immune node deployment algorithm. In Electrical and Computer Engineering (CCECE), 2014 IEEE 27th Canadian Conference on (pp. 1-6). IEEE.
7 Jung Eui-chul, gimsangyun, gimon, & jogiryang. (2012). Optimal orientation of the composite linear array source. Journal of Korea Information and Communications Society, 37 (4), 250-259.
8 Jeong, E. C., Kim, S. Y., Kim, O., & Cho, K. R. (2012). Optimal Directivity Synthesis of Linear array Sources. The Journal of Korean Institute of Communications and Information Sciences, 37(4A), 250-259.
9 Miao Guang Kai, Kong Zhepeng, & Yanhong. (2012). Optimization function distributed immune evolutionary algorithm. Systems Engineering and Electronics, 34 (2), 413-417.
10 Abo-Zahhad, M., Ahmed, S. M., Sabor, N., & Al-Ajlouni, A. F. (2012). A New Method for Fastening the Convergence of Immune Algorithms Using an Adaptive Mutation Approach.
11 Jung Eui-chul, gimsangyun, gimon, and jogiryang. (2012). Optimal directional synthesis of linear array source. The Journal of Korea Information and Communications Society, 37 (4), 250-259.
12 Miao Qi wide Kongzhe Peng, & Yanhong. (2012). Optimization function distributed immune evolutionary algorithm. Systems Engineering and Electronics, 34 (2), 413-417.
1 Google Scholar 
2 CiteSeerX 
3 refSeek 
4 iSEEK 
5 Socol@r  
6 Scribd 
7 SlideShare 
8 PDFCAST 
9 PdfSR 
M. Abo Zahhad, S. M. Ahmed, N. Sabor and A. F. Al Ajlouni, "Design of Two-Dimensional Recursive Digital Filters with Specified Magnitude and Group Delay Characteristics using Taguchi-based Immune Algorithm", Int. J. of Signal and Imaging Systems Engineering, vol. 3, no. 3, 2010
A. H. Aly, M. M. Fahmy. "Design of Two Dimensional Recursive Digital Filters with Specified Magnitude and Group Delay Characteristics". IEEE Trans. on Circuits and Systems, 25(11): 908
A. Kalinli, N. Karaboga. "Artificial immune algorithm for IIR filters design". Engineering Applications of Artificial Intelligance, 18(8): 919
Alex A. Freitas, Jon Timmis. “Revisiting the Foundations of Arti?cial Immune Systems for Data Mining”. IEEE Trans. on Evolutionary Compuation, 11(4): 521
F. Vafaee, P.C. Nelson. “A Genetic Algorithm that Incorporates an Adaptive Mutation Based on an Evolutionary Model”, International Conference on Machine Learning and Applications, Miami Beach, FL, December 2009.
G. Zilong, W. Sun’an, Z. Jian. "A novel Immune Evolutionary Algorithm Incorporating Chaos Optimization". Pattern Recognition Letter, 27(1): 2:8, January 2006
J. T. Tsai ,W. Ho ,T.K. Liu, J. H. Chou. "Improved immune algorithm for global numerical optimization and job-shop scheduling problems ". Applied Mathematics and Computation, 194(2): 406 424, December 2007
J. T. Tsai, J. H. Chou. “Design of Optimal Digital IIR Filters by Using an Improved Immune Algorithm”. IEEE Trans. signal processing, 54(12): 4582–4596, December 2006
J. T. Tsai, W. H. Ho, J. H. Chou. “Design of Two-Dimensional Recursive Filters by Using Taguchi Immune Algorithm”. IET signal process, 2(2):110
K. Kaur, A. Chhabra, G. Singh. "Heuristics Based Genetic Algorithm for Scheduling Static Tasks in Homogeneous Parallel System". International Journal of Computer Science and Security, 4(2): 183 198, May 2010.
M. Bazaraa, J. Jarvis, H. Sherali. "Linear Programming and Network Flows". John Wiley & Sons, New York (1990)
M. VillalobosArias, C. A. Coello, O. Hernandez Lerma. ”Convergence Analysis of a Multiobjective Arti?cial Immune System Algorithm”. In Nicosia et al. (eds) Proc. Int. Conf. Arti?cial Immune Systems (ICARIS 2004), LNCS, Springer, 3239: 226 235, 2004
M. VillalobosArias, C. A. Coello, O. Hernandez-Lerma. “Asymptotic convergence of some metaheuristics used for multiobjective optimization”. LNCS, Springer, 3469: 95-111, 2005
Roy Danchick. “Accurate numerical partials with applications to optimization”, Applied mathematics and computation, 183(1): 551
V. Cutello, G. Nicosia, M. Romeo, P.S. Oliveto. “On the convergence of immune algorithm”. IEEE Symposium on Foundations of Computational Intelligence: 409
Z. Michalewiz. "Genetic Algorithm and Data Structure". Springer
Professor Prof. M. Abo-Zahhad
Assiut University - Egypt
zahhad@yahoo.com
Mr. Sabah M. Ahmed
- Egypt
Mr. Nabil Sabor
- Egypt
Mr. Ahmad F. Al-Ajlouni
-


CREATE AUTHOR ACCOUNT
 
LAUNCH YOUR SPECIAL ISSUE
View all special issues >>
 
PUBLICATION VIDEOS