Manta ray foraging optimization with quasi-reflected opposition strategy for global optimization

Abdul Razak, Ahmad Azwan and Nasir, Ahmad Nor Kasruddin and Abd Ghani, N. M. and Mat Jusof, Mohd Falfazli (2022) Manta ray foraging optimization with quasi-reflected opposition strategy for global optimization. In: Lecture Notes in Electrical Engineering; 6th International Conference on Electrical, Control and Computer Engineering, InECCE 2021 , 23 August 2021 , Kuantan, Pahang. 477 -485., 842. ISSN 1876-1100 ISBN 978-981168689-4

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Abstract

This paper proposes an extension of Manta Ray Foraging Optimization (MRFO) using Oppositional-based Learning (OBL) technique called Quasi Reflected Opposition (QRO). MRFO is a new algorithm that developed based on the nature of a species in cartilaginous fish called Manta Ray. Manta ray employs three foraging strategies which are chain, cyclone and somersault foraging. Nonetheless, MRFO is tends to getting trap into local optima due to the redundant of intensification of the search agents in the search space. On the other side, OBL is a prominent technique in reducing chance of local optimum while increasing the convergence speed. Thus, QRO is synergized into MRFO to form QR-MRFO, in objective to improve MRFO in term of finding better accuracy of solution and faster convergence rate. Latter, QR-MRFO was performed on a series of benchmark functions and analyzed using statistical non-parametric test of Wilcoxon to measure the significant level of improvement. Results from the test shows that MRFO is undoubtedly defeated by QR-MRFO in term of accuracy.

Item Type:	Conference or Workshop Item (Paper)
Additional Information:	Indexed by Scopus
Uncontrolled Keywords:	Accuracy; Convergence; Manta ray; Optimization; Quasi-opposition-based Learning; Single-objective; Spiral
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division:	Institute of Postgraduate Studies Faculty of Electrical and Electronic Engineering Technology
Depositing User:	Mrs Norsaini Abdul Samat
Date Deposited:	03 Oct 2022 02:55
Last Modified:	03 Oct 2022 02:55
URI:	http://umpir.ump.edu.my/id/eprint/35299
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