A Comparative Study of Metaheuristic Optimization Algorithms for Solving Real-World Engineering Design Problems

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dc.contributor.authorAltay E.V.
dc.contributor.authorAltay O.
dc.contributor.authorÖzçevik Y.
dc.date.accessioned2024-07-22T08:03:08Z
dc.date.available2024-07-22T08:03:08Z
dc.date.issued2023
dc.description.abstractReal-world engineering design problems with complex objective functions under some constraints are relatively difficult problems to solve. Such design problems are widely experienced in many engineering fields, such as industry, automotive, construction, machinery, and interdisciplinary research. However, there are established optimization techniques that have shown effectiveness in addressing these types of issues. This research paper gives a comparative study of the implementation of seventeen new metaheuristic methods in order to optimize twelve distinct engineering design issues. The algorithms used in the study are listed as: transient search optimization (TSO), equilibrium optimizer (EO), grey wolf optimizer (GWO), moth-flame optimization (MFO), whale optimization algorithm (WOA), slime mould algorithm (SMA), harris hawks optimization (HHO), chimp optimization algorithm (COA), coot optimization algorithm (COOT), multi-verse optimization (MVO), arithmetic optimization algorithm (AOA), aquila optimizer (AO), sine cosine algorithm (SCA), smell agent optimization (SAO), and seagull optimization algorithm (SOA), pelican optimization algorithm (POA), and coati optimization algorithm (CA). As far as we know, there is no comparative analysis of recent and popular methods against the concrete conditions of real-world engineering problems. Hence, a remarkable research guideline is presented in the study for researchers working in the fields of engineering and artificial intelligence, especially when applying the optimization methods that have emerged recently. Future research can rely on this work for a literature search on comparisons of metaheuristic optimization methods in real-world problems under similar conditions. © 2023 Tech Science Press. All rights reserved.
dc.identifier.DOI-ID10.32604/cmes.2023.029404
dc.identifier.issn15261492
dc.identifier.urihttp://akademikarsiv.cbu.edu.tr:4000/handle/123456789/12145
dc.language.isoEnglish
dc.publisherTech Science Press
dc.rightsAll Open Access; Hybrid Gold Open Access
dc.subjectDesign aids
dc.subjectEngineering research
dc.subjectMachine design
dc.subjectEngineering design problems
dc.subjectMetaheuristic optimization
dc.subjectMetaheuristic optimization algorithm
dc.subjectMulti-disciplinary designs
dc.subjectOptimisations
dc.subjectOptimization algorithms
dc.subjectOptimization problems
dc.subjectOptimizers
dc.subjectReal-world
dc.subjectReal-world engineering design problem
dc.subjectOptimization
dc.titleA Comparative Study of Metaheuristic Optimization Algorithms for Solving Real-World Engineering Design Problems
dc.typeArticle

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