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...

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Main Authors:	Mohd Helmi, Suid, Mohd Riduwan, Ghazali, Mohd Ashraf, Ahmad, Irawan, Addie, Raja Mohd Taufika, Raja Ismail, Mohd Zaidi, Mohd Tumari
Format:	Conference or Workshop Item
Language:	English English
Published:	Universiti Malaysia Pahang 2018
Subjects:	TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://umpir.ump.edu.my/id/eprint/24128/ http://umpir.ump.edu.my/id/eprint/24128/ 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

id	ump-24128
recordtype	eprints
spelling	ump-241282019-05-21T01:46:39Z 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 Irawan, Addie 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 Irawan, Addie 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
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English English
topic	TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	TK Electrical engineering. Electronics Nuclear engineering Mohd Helmi, Suid Mohd Riduwan, Ghazali Mohd Ashraf, Ahmad Irawan, Addie Raja Mohd Taufika, Raja Ismail Mohd Zaidi, Mohd Tumari An improved sine cosine algorithm for solving optimization problems
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.
format	Conference or Workshop Item
author	Mohd Helmi, Suid Mohd Riduwan, Ghazali Mohd Ashraf, Ahmad Irawan, Addie Raja Mohd Taufika, Raja Ismail Mohd Zaidi, Mohd Tumari
author_facet	Mohd Helmi, Suid Mohd Riduwan, Ghazali Mohd Ashraf, Ahmad Irawan, Addie Raja Mohd Taufika, Raja Ismail Mohd Zaidi, Mohd Tumari
author_sort	Mohd Helmi, Suid
title	An improved sine cosine algorithm for solving optimization problems
title_short	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_sort	improved sine cosine algorithm for solving optimization problems
publisher	Universiti Malaysia Pahang
publishDate	2018
url	http://umpir.ump.edu.my/id/eprint/24128/ http://umpir.ump.edu.my/id/eprint/24128/ 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
first_indexed	2023-09-18T22:36:21Z
last_indexed	2023-09-18T22:36:21Z
_version_	1777416622048280576

An improved sine cosine algorithm for solving optimization problems

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