2020
DOI: 10.1016/j.engappai.2019.103300
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Manta ray foraging optimization: An effective bio-inspired optimizer for engineering applications

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Cited by 786 publications
(465 citation statements)
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“…MRFO is a novel bio-inspired based optimizer which is inspired based on the activities of menta rays which imitates the key strategies of foraging such as chaining, cyclone and somersault. 46 The MRFO can solve multimodal single objective engineering optimization problems. Similar to other challenging methodologies, the initial step of the MRFO is the random initialization process as expressed in Equation (11).…”
Section: Mrfomentioning
confidence: 99%
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“…MRFO is a novel bio-inspired based optimizer which is inspired based on the activities of menta rays which imitates the key strategies of foraging such as chaining, cyclone and somersault. 46 The MRFO can solve multimodal single objective engineering optimization problems. Similar to other challenging methodologies, the initial step of the MRFO is the random initialization process as expressed in Equation (11).…”
Section: Mrfomentioning
confidence: 99%
“…The MRFO has successfully been used to solve different benchmark optimization problems and real-world design problems such as tension spring design, pressure vessel design, welded beam design, speed reducer design, rolling element bearing design, multiple disc clutch brake design, and belleville spring design. 46 In this article, MRFO is applied to solve the adopted optimization problem to define the seven unidentified parameters of PEMFCs models. Three test study cases using typical commercial stacks are analyzed to examine the performance of MRFO complete with necessary comparisons and further validations.…”
mentioning
confidence: 99%
“…7). MRFO is a bio-inspired optimization algorithm, and its conduct depicts three foraging characteristics of Manta rays for developing a proficient optimization standard for solving unusual optimization problems [33]. x i ( t + 1 )…”
Section: F Mrfomentioning
confidence: 99%
“…MRFO believes that the finest solution so far is the location with the highest plankton. The chain foraging mathematical model is depicted as [33]:…”
Section: ) Chain Foragingmentioning
confidence: 99%
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