An improved nature inspired levy dingo optimization algorithm for multidisciplinary engineering design problems

The hunting strategy of Dingo (Australian Dog) inspired a newly developed metaheuristic optimization technique called Dingo Optimization algorithm. Using the basic concept of this current approach, a hybrid form known as the Levy dingo Optimization algorithm is created. This new levy function-based...

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Hauptverfasser: Mishra, Tanuj, Singh, Amit Kumar, Kamboj, Vikram Kumar
Format: Tagungsbericht
Sprache:eng
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Zusammenfassung:The hunting strategy of Dingo (Australian Dog) inspired a newly developed metaheuristic optimization technique called Dingo Optimization algorithm. Using the basic concept of this current approach, a hybrid form known as the Levy dingo Optimization algorithm is created. This new levy function-based technique is devised to boost local search capacity during the exploration phase. This algorithm is effectively validated on nonlinear and constrained multidisciplinary engineering applications and standard benchmark functions. The recommended solution LDOA has been verified and providing optimal solutions as compare to other search algorithms including hHHO-SCA, SCA, HS, GA, GSA etc. and there is a neck-to-neck competition with some of the techniques like GWO, PSO etc. This method is put to the test on four engineering problems: speed reducers, welded beams, pressure vessels, and tension/compression spring design. The resulting results are compared to various well-known approaches.
ISSN:0094-243X
1551-7616
DOI:10.1063/5.0162825