Abstract
In multi-objective optimization computing, it is important to assign suitable parameters to each optimization problem to obtain better solutions. In this study, a self-adaptive multi-objective harmony search (SaMOHS) algorithm is developed to apply the parameter-setting-free technique, which is an example of a self-adaptive methodology. The SaMOHS algorithm attempts to remove some of the inconvenience from parameter setting and selects the most adaptive parameters during the iterative solution search process. To verify the proposed algorithm, an optimal least cost water distribution network design problem is applied to three different target networks. The results are compared with other well-known algorithms such as multi-objective harmony search and the non-dominated sorting genetic algorithm-II. The efficiency of the proposed algorithm is quantified by suitable performance indices. The results indicate that SaMOHS can be efficiently applied to the search for Pareto-optimal solutions in a multi-objective solution space.
| Original language | English |
|---|---|
| Pages (from-to) | 1-21 |
| Number of pages | 21 |
| Journal | Engineering Optimization |
| DOIs | |
| Publication status | Accepted/In press - 2017 Jan 21 |
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Keywords
- multi-objective harmony search
- Optimal design of water distribution network
- parameter-setting-free
- self-adaptive
ASJC Scopus subject areas
- Computer Science Applications
- Control and Optimization
- Management Science and Operations Research
- Industrial and Manufacturing Engineering
- Applied Mathematics
Cite this
Self-adaptive multi-objective harmony search for optimal design of water distribution networks. / Choi, Young Hwan; Lee, Ho Min; Yoo, Do Guen; Kim, Joong Hoon.
In: Engineering Optimization, 21.01.2017, p. 1-21.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Self-adaptive multi-objective harmony search for optimal design of water distribution networks
AU - Choi, Young Hwan
AU - Lee, Ho Min
AU - Yoo, Do Guen
AU - Kim, Joong Hoon
PY - 2017/1/21
Y1 - 2017/1/21
N2 - In multi-objective optimization computing, it is important to assign suitable parameters to each optimization problem to obtain better solutions. In this study, a self-adaptive multi-objective harmony search (SaMOHS) algorithm is developed to apply the parameter-setting-free technique, which is an example of a self-adaptive methodology. The SaMOHS algorithm attempts to remove some of the inconvenience from parameter setting and selects the most adaptive parameters during the iterative solution search process. To verify the proposed algorithm, an optimal least cost water distribution network design problem is applied to three different target networks. The results are compared with other well-known algorithms such as multi-objective harmony search and the non-dominated sorting genetic algorithm-II. The efficiency of the proposed algorithm is quantified by suitable performance indices. The results indicate that SaMOHS can be efficiently applied to the search for Pareto-optimal solutions in a multi-objective solution space.
AB - In multi-objective optimization computing, it is important to assign suitable parameters to each optimization problem to obtain better solutions. In this study, a self-adaptive multi-objective harmony search (SaMOHS) algorithm is developed to apply the parameter-setting-free technique, which is an example of a self-adaptive methodology. The SaMOHS algorithm attempts to remove some of the inconvenience from parameter setting and selects the most adaptive parameters during the iterative solution search process. To verify the proposed algorithm, an optimal least cost water distribution network design problem is applied to three different target networks. The results are compared with other well-known algorithms such as multi-objective harmony search and the non-dominated sorting genetic algorithm-II. The efficiency of the proposed algorithm is quantified by suitable performance indices. The results indicate that SaMOHS can be efficiently applied to the search for Pareto-optimal solutions in a multi-objective solution space.
KW - multi-objective harmony search
KW - Optimal design of water distribution network
KW - parameter-setting-free
KW - self-adaptive
UR - http://www.scopus.com/inward/record.url?scp=85010679789&partnerID=8YFLogxK
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U2 - 10.1080/0305215X.2016.1273910
DO - 10.1080/0305215X.2016.1273910
M3 - Article
AN - SCOPUS:85010679789
SP - 1
EP - 21
JO - Engineering Optimization
JF - Engineering Optimization
SN - 0305-215X
ER -