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Arit Thammano. A self-adaptive differential evolution algorithm for solving optimization problems. (). King Mongkut's University of Technology North Bangkok. Central Library. : , 2022.
A self-adaptive differential evolution algorithm for solving optimization problems
Name: Farda, Irfan
Organization :
King Mongkut's Institute of Technology Ladkrabang. Faculty of Information Technology
Email :
64607042@kmitl.ac.th
Name: Arit Thammano
Organization :
King Mongkut's Institute of Technology Ladkrabang. Faculty of Information Technology
Email :
arit@it.kmitl.ac.th
LCSH:
Differential equations
LCSH:
Algorithms
Abstract:
This research proposes a novel self-adaptive differential evolution algorithm for solving continuous optimization problems. This paper focuses on redesiging the self-adaptive strategy for the mutation parameters. The new mutation parameters adjust themselves to the current situation of the algorithm. When the search is stagnant, the first mutation parameter that scales the difference between the best vector and the target vector will be increased. In contrast, the second mutation parameter that scales the difference between two random target vectors will be decreased. On the other hand, when the search progresses well towards the global optimum, the algorithm will enhance the search of the surrounding space by doing the opposite of the above actions. The performance of the proposed self-adaptive differential evolution algorithmwas evaluated and compared with the classic differential evolution algorithm on 7 benchmark functions. The experimental results showed that the proposed algorithm converged much faster than the classic differential evolution algorithm on all benchmark functions.
King Mongkut's University of Technology North Bangkok. Central Library
Address:
BANGKOK
Email:
library@kmutnb.ac.th
Created:
2022
Modified:
2022-12-27
Issued:
2022-12-27
บทความ/Article
application/pdf
BibliograpyCitation :
In King Mongkut's University of Technology North Bangkok. Faculty of Information Technology. The 18th International Conference on Computing and Information Technology (IC2IT 2022) (pp.68-76). Cham, Switzerland : Springer
eng
©copyrights King Mongkut's University of Technology North Bangkok
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ใช้เวลา
0.023738 วินาที
Farda, Irfan
| Title | Contributor | Type |
|---|---|---|
| A self-adaptive differential evolution algorithm for solving optimization problems
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Farda, Irfan;Arit Thammano | บทความ/Article |
Arit Thammano
| Title | Contributor | Type |
|---|---|---|
| Modified ant system with threshold for the vehicle routing problem
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Petcharat Rungwachira;Arit Thammano | บทความ/Article | |
| A self-adaptive differential evolution algorithm for solving optimization problems
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Farda, Irfan;Arit Thammano | บทความ/Article | |
| Enhancing genetic algorithm performance with hybrid strategy for solving optimization problems
มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ Irfan Farda;Arit Thammano | บทความ/Article | |
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