Non-dominated sorting Harris's hawk multi-objective optimizer based on reference point approach
A non-dominated sorting Harris's hawk multi-objective optimizer (NDSHHMO) algorithm is presented in this paper. The algorithm is able to improve the population diversity, convergence of non-dominated solutions toward the Pareto front, and prevent the population from trapping into local optimal....
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| Format: | EJournal Article |
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Institute of Advanced Engineering and Science,
2019-09-01.
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| LEADER | 02391 am a22003013u 4500 | ||
|---|---|---|---|
| 001 | ijeecs18415_12983 | ||
| 042 | |a dc | ||
| 100 | 1 | 0 | |a Yasear, Shaymah Akram |e author |
| 100 | 1 | 0 | |e contributor |
| 700 | 1 | 0 | |a Ku-Mahamud, Ku Ruhana |e author |
| 245 | 0 | 0 | |a Non-dominated sorting Harris's hawk multi-objective optimizer based on reference point approach |
| 260 | |b Institute of Advanced Engineering and Science, |c 2019-09-01. | ||
| 500 | |a https://ijeecs.iaescore.com/index.php/IJEECS/article/view/18415 | ||
| 520 | |a A non-dominated sorting Harris's hawk multi-objective optimizer (NDSHHMO) algorithm is presented in this paper. The algorithm is able to improve the population diversity, convergence of non-dominated solutions toward the Pareto front, and prevent the population from trapping into local optimal. This was achieved by integrating fast non-dominated sorting with the original Harris's hawk multi-objective optimizer (HHMO). Non-dominated sorting divides the objective space into levels based on fitness values and then selects non-dominated solutions to produce the next generation of hawks. A set of well-known multi-objective optimization problems has been used to evaluate the performance of the proposed NDSHHMO algorithm. The results of the NDSHHMO algorithm were verified against the results of an HHMO algorithm. Experimental results demonstrate the efficiency of the proposed NDSHHMO algorithm in terms of enhancing the ability of convergence toward the Pareto front and significantly improve the search ability of the HHMO. | ||
| 540 | |a Copyright (c) 2019 Institute of Advanced Engineering and Science | ||
| 540 | |a http://creativecommons.org/licenses/by-nc/4.0 | ||
| 546 | |a eng | ||
| 690 | |a Computer Science; artificial Intelligence; swarm intelligence | ||
| 690 | |a Swarm-intelligence; Global optimization; Metaheuristic; Optimization algorithm | ||
| 655 | 7 | |a info:eu-repo/semantics/article |2 local | |
| 655 | 7 | |a info:eu-repo/semantics/publishedVersion |2 local | |
| 655 | 7 | |2 local | |
| 786 | 0 | |n Indonesian Journal of Electrical Engineering and Computer Science; Vol 15, No 3: September 2019; 1603-1614 | |
| 786 | 0 | |n 2502-4760 | |
| 786 | 0 | |n 2502-4752 | |
| 786 | 0 | |n 10.11591/ijeecs.v15.i3 | |
| 787 | 0 | |n https://ijeecs.iaescore.com/index.php/IJEECS/article/view/18415/12983 | |
| 856 | 4 | 1 | |u https://ijeecs.iaescore.com/index.php/IJEECS/article/view/18415/12983 |z Get fulltext |