Abstract
The particle swarm optimization (PSO) is a natural-inspire optimization algorithm mimicking the movement behavior of animal flocks for food searching. Although the algorithm presents some advantages and widely application, however, there are several drawbacks such as trapping in local optima and immature convergence rate. To overcome these disadvantages, many improved versions of PSO have been proposed. One of the latest variants is the extraordinary particle swarm optimization (EPSO). The particles in the EPSO are assigned to move toward their own determined target through the search space. The applicability of EPSO is verified by several experiments in engineering optimization problems. The application results show the outperformance of the EPSO than the other PSO variants in terms of solution searching and as well as convergence rate.
| Original language | English |
|---|---|
| Title of host publication | Harmony Search Algorithm - Proceedings of the 3rd International Conference on Harmony Search Algorithm (ICHSA 2017) |
| Publisher | Springer Verlag |
| Pages | 35-41 |
| Number of pages | 7 |
| Volume | 514 |
| ISBN (Print) | 9789811037276 |
| DOIs | |
| Publication status | Published - 2017 |
| Event | Proceedings of the 3rd International Conference on Harmony Search Algorithm, ICHSA 2017 - Bilbao, Spain Duration: 2017 Feb 22 → 2017 Feb 24 |
Publication series
| Name | Advances in Intelligent Systems and Computing |
|---|---|
| Volume | 514 |
| ISSN (Print) | 21945357 |
Other
| Other | Proceedings of the 3rd International Conference on Harmony Search Algorithm, ICHSA 2017 |
|---|---|
| Country | Spain |
| City | Bilbao |
| Period | 17/2/22 → 17/2/24 |
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Keywords
- Engineering optimization problem
- Extraordinary particle swarm optimization
- Urban drainage system
ASJC Scopus subject areas
- Control and Systems Engineering
- Computer Science(all)
Cite this
The extraordinary particle swarm optimization and its application in constrained engineering problems. / Ngo, Thi Thuy; Sadollah, Ali; Yoo, Do Guen; Choo, Yeon Moon; Jun, Sang Hoon; Kim, Joong Hoon.
Harmony Search Algorithm - Proceedings of the 3rd International Conference on Harmony Search Algorithm (ICHSA 2017). Vol. 514 Springer Verlag, 2017. p. 35-41 (Advances in Intelligent Systems and Computing; Vol. 514).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - The extraordinary particle swarm optimization and its application in constrained engineering problems
AU - Ngo, Thi Thuy
AU - Sadollah, Ali
AU - Yoo, Do Guen
AU - Choo, Yeon Moon
AU - Jun, Sang Hoon
AU - Kim, Joong Hoon
PY - 2017
Y1 - 2017
N2 - The particle swarm optimization (PSO) is a natural-inspire optimization algorithm mimicking the movement behavior of animal flocks for food searching. Although the algorithm presents some advantages and widely application, however, there are several drawbacks such as trapping in local optima and immature convergence rate. To overcome these disadvantages, many improved versions of PSO have been proposed. One of the latest variants is the extraordinary particle swarm optimization (EPSO). The particles in the EPSO are assigned to move toward their own determined target through the search space. The applicability of EPSO is verified by several experiments in engineering optimization problems. The application results show the outperformance of the EPSO than the other PSO variants in terms of solution searching and as well as convergence rate.
AB - The particle swarm optimization (PSO) is a natural-inspire optimization algorithm mimicking the movement behavior of animal flocks for food searching. Although the algorithm presents some advantages and widely application, however, there are several drawbacks such as trapping in local optima and immature convergence rate. To overcome these disadvantages, many improved versions of PSO have been proposed. One of the latest variants is the extraordinary particle swarm optimization (EPSO). The particles in the EPSO are assigned to move toward their own determined target through the search space. The applicability of EPSO is verified by several experiments in engineering optimization problems. The application results show the outperformance of the EPSO than the other PSO variants in terms of solution searching and as well as convergence rate.
KW - Engineering optimization problem
KW - Extraordinary particle swarm optimization
KW - Urban drainage system
UR - http://www.scopus.com/inward/record.url?scp=85012186663&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85012186663&partnerID=8YFLogxK
U2 - 10.1007/978-981-10-3728-3_5
DO - 10.1007/978-981-10-3728-3_5
M3 - Conference contribution
AN - SCOPUS:85012186663
SN - 9789811037276
VL - 514
T3 - Advances in Intelligent Systems and Computing
SP - 35
EP - 41
BT - Harmony Search Algorithm - Proceedings of the 3rd International Conference on Harmony Search Algorithm (ICHSA 2017)
PB - Springer Verlag
ER -