Abstract
Various evolutionary algorithms are being developed to search the optimal solution of various problems in the real world. Evolutionary algorithms search solutions showing the optimal fitness to given problem using their own operators. Engineering benchmark problems can be used for performance measurement of evolutionary algorithms, and the water distribution network design problem is one of the widely used benchmark problems. In this study, the water distribution network design problems are generated by modifications of five problem characteristic factors. Generated benchmark problems are applied to quantitatively evaluate the performance among evolutionary algorithms. Each algorithm shows its own strength and weakness. Optimization results show that the engineering benchmark generation method suggested in this study can be served as a reliable framework for comparison of performances on various water distribution network design problems.
| Original language | English |
|---|---|
| Title of host publication | 2017 IEEE Congress on Evolutionary Computation, CEC 2017 - Proceedings |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 714-717 |
| Number of pages | 4 |
| ISBN (Electronic) | 9781509046010 |
| DOIs | |
| Publication status | Published - 2017 Jul 5 |
| Event | 2017 IEEE Congress on Evolutionary Computation, CEC 2017 - Donostia-San Sebastian, Spain Duration: 2017 Jun 5 → 2017 Jun 8 |
Other
| Other | 2017 IEEE Congress on Evolutionary Computation, CEC 2017 |
|---|---|
| Country | Spain |
| City | Donostia-San Sebastian |
| Period | 17/6/5 → 17/6/8 |
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Keywords
- Engineering approach
- Evolutionary algorithms
- Performance comparison
- Water distribution networks
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Networks and Communications
- Computer Science Applications
- Signal Processing
Cite this
Engineering benchmark generation and performance measurement of evolutionary algorithms. / Kim, Joong Hoon; Lee, Ho Min; Jung, Donghwi; Sadollah, Ali.
2017 IEEE Congress on Evolutionary Computation, CEC 2017 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. p. 714-717 7969380.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Engineering benchmark generation and performance measurement of evolutionary algorithms
AU - Kim, Joong Hoon
AU - Lee, Ho Min
AU - Jung, Donghwi
AU - Sadollah, Ali
PY - 2017/7/5
Y1 - 2017/7/5
N2 - Various evolutionary algorithms are being developed to search the optimal solution of various problems in the real world. Evolutionary algorithms search solutions showing the optimal fitness to given problem using their own operators. Engineering benchmark problems can be used for performance measurement of evolutionary algorithms, and the water distribution network design problem is one of the widely used benchmark problems. In this study, the water distribution network design problems are generated by modifications of five problem characteristic factors. Generated benchmark problems are applied to quantitatively evaluate the performance among evolutionary algorithms. Each algorithm shows its own strength and weakness. Optimization results show that the engineering benchmark generation method suggested in this study can be served as a reliable framework for comparison of performances on various water distribution network design problems.
AB - Various evolutionary algorithms are being developed to search the optimal solution of various problems in the real world. Evolutionary algorithms search solutions showing the optimal fitness to given problem using their own operators. Engineering benchmark problems can be used for performance measurement of evolutionary algorithms, and the water distribution network design problem is one of the widely used benchmark problems. In this study, the water distribution network design problems are generated by modifications of five problem characteristic factors. Generated benchmark problems are applied to quantitatively evaluate the performance among evolutionary algorithms. Each algorithm shows its own strength and weakness. Optimization results show that the engineering benchmark generation method suggested in this study can be served as a reliable framework for comparison of performances on various water distribution network design problems.
KW - Engineering approach
KW - Evolutionary algorithms
KW - Performance comparison
KW - Water distribution networks
UR - http://www.scopus.com/inward/record.url?scp=85027895913&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85027895913&partnerID=8YFLogxK
U2 - 10.1109/CEC.2017.7969380
DO - 10.1109/CEC.2017.7969380
M3 - Conference contribution
AN - SCOPUS:85027895913
SP - 714
EP - 717
BT - 2017 IEEE Congress on Evolutionary Computation, CEC 2017 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
ER -