Abstract
Artificial immune system (AIS) is one of the nature-inspired algorithm for optimization problem. In AIS, clonal selection algorithm (CSA) is able to improve global searching ability. However, the CSA convergence and accuracy can be further improved because the hypermutation in CSA itself cannot always guarantee a better solution. Alternatively, Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO) have been used efficiently in solving complex optimization problems, but they have a tendency to converge prematurely. Thus, a hybrid PSO-AIS and a new external memory CSA based scheme called EMCSA are proposed. In hybrid PSO-AIS, the good features of PSO and AIS are combined in order to reduce any limitation. Alternatively, EMCSA captures all the best antibodies into the memory in order to enhance global searching capability. In this preliminary study, the results show that the performance of hybrid PSO-AIS compares favourably with other algorithms while EMCSA produced moderate results in most of the simulations.
| Original language | English |
|---|---|
| Title of host publication | ISCI 2011 - 2011 IEEE Symposium on Computers and Informatics |
| Pages | 12-17 |
| Number of pages | 6 |
| DOIs | |
| Publication status | Published - 01 Sep 2011 |
| Event | 2011 IEEE Symposium on Computers and Informatics, ISCI 2011 - Kuala Lumpur, Malaysia Duration: 20 Mar 2011 → 22 Mar 2011 |
Other
| Other | 2011 IEEE Symposium on Computers and Informatics, ISCI 2011 |
|---|---|
| Country | Malaysia |
| City | Kuala Lumpur |
| Period | 20/03/11 → 22/03/11 |
Fingerprint
All Science Journal Classification (ASJC) codes
- Computer Networks and Communications
- Information Systems
Cite this
}
Artificial immune system based on hybrid and external memory for mathematical function optimization. / Yap, David F.W.; Koh, Johnny Siaw Paw; Tiong, Sieh Kiong.
ISCI 2011 - 2011 IEEE Symposium on Computers and Informatics. 2011. p. 12-17 5958875.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Artificial immune system based on hybrid and external memory for mathematical function optimization
AU - Yap, David F.W.
AU - Koh, Johnny Siaw Paw
AU - Tiong, Sieh Kiong
PY - 2011/9/1
Y1 - 2011/9/1
N2 - Artificial immune system (AIS) is one of the nature-inspired algorithm for optimization problem. In AIS, clonal selection algorithm (CSA) is able to improve global searching ability. However, the CSA convergence and accuracy can be further improved because the hypermutation in CSA itself cannot always guarantee a better solution. Alternatively, Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO) have been used efficiently in solving complex optimization problems, but they have a tendency to converge prematurely. Thus, a hybrid PSO-AIS and a new external memory CSA based scheme called EMCSA are proposed. In hybrid PSO-AIS, the good features of PSO and AIS are combined in order to reduce any limitation. Alternatively, EMCSA captures all the best antibodies into the memory in order to enhance global searching capability. In this preliminary study, the results show that the performance of hybrid PSO-AIS compares favourably with other algorithms while EMCSA produced moderate results in most of the simulations.
AB - Artificial immune system (AIS) is one of the nature-inspired algorithm for optimization problem. In AIS, clonal selection algorithm (CSA) is able to improve global searching ability. However, the CSA convergence and accuracy can be further improved because the hypermutation in CSA itself cannot always guarantee a better solution. Alternatively, Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO) have been used efficiently in solving complex optimization problems, but they have a tendency to converge prematurely. Thus, a hybrid PSO-AIS and a new external memory CSA based scheme called EMCSA are proposed. In hybrid PSO-AIS, the good features of PSO and AIS are combined in order to reduce any limitation. Alternatively, EMCSA captures all the best antibodies into the memory in order to enhance global searching capability. In this preliminary study, the results show that the performance of hybrid PSO-AIS compares favourably with other algorithms while EMCSA produced moderate results in most of the simulations.
UR - http://www.scopus.com/inward/record.url?scp=80052129975&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=80052129975&partnerID=8YFLogxK
U2 - 10.1109/ISCI.2011.5958875
DO - 10.1109/ISCI.2011.5958875
M3 - Conference contribution
SN - 9781612846903
SP - 12
EP - 17
BT - ISCI 2011 - 2011 IEEE Symposium on Computers and Informatics
ER -