An improved sine cosine algorithm for solving optimization problems
Due to its simplicity and less tedious parameter tuning over other multi-agent-based optimization algorithms, Sine Cosine Algorithm (SCA) has gained lots of attention from numerous researchers for solving optimization problem. However, the existing SCA tends to have low optimization precision and lo...
| Main Authors: | , , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English English |
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Universiti Malaysia Pahang
2018
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| Online Access: | http://umpir.ump.edu.my/id/eprint/24128/2/13.1%20An%20improved%20sine%20cosine%20algorithm%20for%20solving.pdf http://umpir.ump.edu.my/id/eprint/24128/13/An%20Improved%20Sine%20Cosine%20Algorithm%20for%20Solving%20Optimization%20Problems.pdf |
| _version_ | 1796993216644382720 |
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| author | Mohd Helmi, Suid Mohd Riduwan, Ghazali Mohd Ashraf, Ahmad Addie Irawan, Hashim Raja Mohd Taufika, Raja Ismail Mohd Zaidi, Mohd Tumari |
| author_facet | Mohd Helmi, Suid Mohd Riduwan, Ghazali Mohd Ashraf, Ahmad Addie Irawan, Hashim Raja Mohd Taufika, Raja Ismail Mohd Zaidi, Mohd Tumari |
| author_sort | Mohd Helmi, Suid |
| collection | UMP |
| description | Due to its simplicity and less tedious parameter tuning over other multi-agent-based optimization algorithms, Sine Cosine Algorithm (SCA) has gained lots of attention from numerous researchers for solving optimization problem. However, the existing SCA tends to have low optimization precision and local minima trapping effect due to the constraint in its exploration and exploitation mechanism. To overcome this drawback, an extensive version of SCA named Improved Sine Cosine Algorithm (iSCA) has been proposed in this work. The main concept is to introduce a nonlinear control strategy to the existing SCA’s exploration and exploitation process in order to synthesize the algorithm’s strength. The effectiveness of this proposed algorithm is evaluated using 23 classical well-known benchmark functions and the results are then verified by a comparative study with several other algorithms namely Ant Lion Optimizer (ALO), Multi-verse Optimization (MVO), Spiral Dynamic Optimization Algorithm (SDA) and Sine Cosine Algorithm (SCA). Experimental results show that the iSCA is very competitive compared to the state-of-the-art meta-heuristic algorithms. |
| first_indexed | 2024-03-06T12:30:54Z |
| format | Conference or Workshop Item |
| id | UMPir24128 |
| institution | Universiti Malaysia Pahang |
| language | English English |
| last_indexed | 2024-03-06T12:30:54Z |
| publishDate | 2018 |
| publisher | Universiti Malaysia Pahang |
| record_format | dspace |
| spelling | UMPir241282020-09-07T09:00:30Z http://umpir.ump.edu.my/id/eprint/24128/ An improved sine cosine algorithm for solving optimization problems Mohd Helmi, Suid Mohd Riduwan, Ghazali Mohd Ashraf, Ahmad Addie Irawan, Hashim Raja Mohd Taufika, Raja Ismail Mohd Zaidi, Mohd Tumari TK Electrical engineering. Electronics Nuclear engineering Due to its simplicity and less tedious parameter tuning over other multi-agent-based optimization algorithms, Sine Cosine Algorithm (SCA) has gained lots of attention from numerous researchers for solving optimization problem. However, the existing SCA tends to have low optimization precision and local minima trapping effect due to the constraint in its exploration and exploitation mechanism. To overcome this drawback, an extensive version of SCA named Improved Sine Cosine Algorithm (iSCA) has been proposed in this work. The main concept is to introduce a nonlinear control strategy to the existing SCA’s exploration and exploitation process in order to synthesize the algorithm’s strength. The effectiveness of this proposed algorithm is evaluated using 23 classical well-known benchmark functions and the results are then verified by a comparative study with several other algorithms namely Ant Lion Optimizer (ALO), Multi-verse Optimization (MVO), Spiral Dynamic Optimization Algorithm (SDA) and Sine Cosine Algorithm (SCA). Experimental results show that the iSCA is very competitive compared to the state-of-the-art meta-heuristic algorithms. Universiti Malaysia Pahang 2018-10 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/24128/2/13.1%20An%20improved%20sine%20cosine%20algorithm%20for%20solving.pdf pdf en http://umpir.ump.edu.my/id/eprint/24128/13/An%20Improved%20Sine%20Cosine%20Algorithm%20for%20Solving%20Optimization%20Problems.pdf Mohd Helmi, Suid and Mohd Riduwan, Ghazali and Mohd Ashraf, Ahmad and Addie Irawan, Hashim and Raja Mohd Taufika, Raja Ismail and Mohd Zaidi, Mohd Tumari (2018) An improved sine cosine algorithm for solving optimization problems. In: IEEE International Conference On Systems, Process And Control (ICSPC 2018) , 14-15 December 2018 , Universiti Malaysia Pahang, Pekan; Pahang. pp. 1-4.. https://doi.org/10.1109/SPC.2018.8703982 |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering Mohd Helmi, Suid Mohd Riduwan, Ghazali Mohd Ashraf, Ahmad Addie Irawan, Hashim Raja Mohd Taufika, Raja Ismail Mohd Zaidi, Mohd Tumari An improved sine cosine algorithm for solving optimization problems |
| title | An improved sine cosine algorithm for solving optimization problems |
| title_full | An improved sine cosine algorithm for solving optimization problems |
| title_fullStr | An improved sine cosine algorithm for solving optimization problems |
| title_full_unstemmed | An improved sine cosine algorithm for solving optimization problems |
| title_short | An improved sine cosine algorithm for solving optimization problems |
| title_sort | improved sine cosine algorithm for solving optimization problems |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
| url | http://umpir.ump.edu.my/id/eprint/24128/2/13.1%20An%20improved%20sine%20cosine%20algorithm%20for%20solving.pdf http://umpir.ump.edu.my/id/eprint/24128/13/An%20Improved%20Sine%20Cosine%20Algorithm%20for%20Solving%20Optimization%20Problems.pdf |
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