Abstract
In the previous companion paper, six new/improved metaheuristic optimization algorithms developed by members of Hydrosystem laboratory in Korea University (KU) are introduced. The six algorithms are Cancer Treatment Algorithm (CTA), Extraordinary Particle Swarm Optimization (EPSO), Improved Cluster HS (ICHS), Multi-Layered HS (MLHS), Sheep Shepherding Algorithm (SSA), and Vision Correction Algorithm (VCA). The six algorithms are tested and compared through six well-known unconstrained benchmark functions and a pipe sizing problem of water distribution network. Performance measures such as mean, best, and worst solutions (under given maximum number of function evaluations) are used for the comparison. Optimization results are obtained from thirty independent optimization trials. Obtained Results show that some of the newly developed/improved algorithms show superior performance with respect to mean, best, and worst solutions when compared to other existing algorithms.
| Original language | English |
|---|---|
| Title of host publication | Advances in Intelligent Systems and Computing |
| Publisher | Springer Verlag |
| Pages | 207-213 |
| Number of pages | 7 |
| Volume | 382 |
| ISBN (Print) | 9783662479254 |
| DOIs | |
| Publication status | Published - 2016 |
| Event | 2nd International Conference on Harmony Search Algorithm, ICHSA 2015 - Seoul, Korea, Republic of Duration: 2015 Aug 19 → 2015 Aug 21 |
Publication series
| Name | Advances in Intelligent Systems and Computing |
|---|---|
| Volume | 382 |
| ISSN (Print) | 21945357 |
Other
| Other | 2nd International Conference on Harmony Search Algorithm, ICHSA 2015 |
|---|---|
| Country | Korea, Republic of |
| City | Seoul |
| Period | 15/8/19 → 15/8/21 |
Fingerprint
Keywords
- Cancer treatment algorithm
- Extraordinary particle swarm optimization
- Improved cluster HS
- Multi-Layered HS
- Sheep shepherding algorithm
- Vision correction algorithm
ASJC Scopus subject areas
- Control and Systems Engineering
- Computer Science(all)
Cite this
KU battle of metaheuristic optimization algorithms 2 : Performance test. / Kim, Joong Hoon; Choi, Young Hwan; Ngo, Thi Thuy; Choi, Jiho; Lee, Ho Min; Choo, Yeon Moon; Lee, Eui Hoon; Yoo, Do Guen; Sadollah, Ali; Jung, Donghwi.
Advances in Intelligent Systems and Computing. Vol. 382 Springer Verlag, 2016. p. 207-213 (Advances in Intelligent Systems and Computing; Vol. 382).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - KU battle of metaheuristic optimization algorithms 2
T2 - Performance test
AU - Kim, Joong Hoon
AU - Choi, Young Hwan
AU - Ngo, Thi Thuy
AU - Choi, Jiho
AU - Lee, Ho Min
AU - Choo, Yeon Moon
AU - Lee, Eui Hoon
AU - Yoo, Do Guen
AU - Sadollah, Ali
AU - Jung, Donghwi
PY - 2016
Y1 - 2016
N2 - In the previous companion paper, six new/improved metaheuristic optimization algorithms developed by members of Hydrosystem laboratory in Korea University (KU) are introduced. The six algorithms are Cancer Treatment Algorithm (CTA), Extraordinary Particle Swarm Optimization (EPSO), Improved Cluster HS (ICHS), Multi-Layered HS (MLHS), Sheep Shepherding Algorithm (SSA), and Vision Correction Algorithm (VCA). The six algorithms are tested and compared through six well-known unconstrained benchmark functions and a pipe sizing problem of water distribution network. Performance measures such as mean, best, and worst solutions (under given maximum number of function evaluations) are used for the comparison. Optimization results are obtained from thirty independent optimization trials. Obtained Results show that some of the newly developed/improved algorithms show superior performance with respect to mean, best, and worst solutions when compared to other existing algorithms.
AB - In the previous companion paper, six new/improved metaheuristic optimization algorithms developed by members of Hydrosystem laboratory in Korea University (KU) are introduced. The six algorithms are Cancer Treatment Algorithm (CTA), Extraordinary Particle Swarm Optimization (EPSO), Improved Cluster HS (ICHS), Multi-Layered HS (MLHS), Sheep Shepherding Algorithm (SSA), and Vision Correction Algorithm (VCA). The six algorithms are tested and compared through six well-known unconstrained benchmark functions and a pipe sizing problem of water distribution network. Performance measures such as mean, best, and worst solutions (under given maximum number of function evaluations) are used for the comparison. Optimization results are obtained from thirty independent optimization trials. Obtained Results show that some of the newly developed/improved algorithms show superior performance with respect to mean, best, and worst solutions when compared to other existing algorithms.
KW - Cancer treatment algorithm
KW - Extraordinary particle swarm optimization
KW - Improved cluster HS
KW - Multi-Layered HS
KW - Sheep shepherding algorithm
KW - Vision correction algorithm
UR - http://www.scopus.com/inward/record.url?scp=84946762025&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84946762025&partnerID=8YFLogxK
U2 - 10.1007/978-3-662-47926-1_20
DO - 10.1007/978-3-662-47926-1_20
M3 - Conference contribution
AN - SCOPUS:84946762025
SN - 9783662479254
VL - 382
T3 - Advances in Intelligent Systems and Computing
SP - 207
EP - 213
BT - Advances in Intelligent Systems and Computing
PB - Springer Verlag
ER -