Abderazek, H.2022-11-212022-11-212019-05-04Abderazek, H. vd. (2019). "A comparative study of recent non-traditional methods for mechanical design optimization". Archives of Computational Methods in Engineering, 27(4), 1031-1048.1134-3060https://doi.org/10.1007/s11831-019-09343-xhttps://link.springer.com/article/10.1007/s11831-019-09343-xhttp://hdl.handle.net/11452/29516Solving practical mechanical problems is considered as a real challenge for evaluating the efficiency of newly developed algorithms. The present article introduces a comparative study on the application of ten recent meta-heuristic approaches to optimize the design of six mechanical engineering optimization problems. The algorithms are: the artificial bee colony (ABC), particle swarm optimization (PSO) algorithm, moth-flame optimization (MFO), ant lion optimizer (ALO), water cycle algorithm (WCA), evaporation rate WCA (ER-WCA), grey wolf optimizer (GWO), mine blast algorithm (MBA), whale optimization algorithm (WOA) and salp swarm algorithm (SSA). The performances of the algorithms are tested quantitatively and qualitatively using convergence speed, solution quality, and the robustness. The experimental results on the six mechanical problems demonstrate the efficiency and the ability of the algorithms used in this article.eninfo:eu-repo/semantics/closedAccessWater cycle algorithmMine blast algorithmStructural designGravitational searchDifferential evolutionImmune algorithmGrey wolfAnt lionCrashworthinesWhaleEfficiencyHeuristic methodsArtificial bee colonies (ABC)Engineering optimization problemsMechanical design optimizationMechanical problemsMeta-heuristic approachMine blast algorithmsOptimization algorithmsParticle swarm optimization algorithmParticle swarm optimization (PSO)Article0005657324000032-s2.0-8506767755310311048274Computer science, interdisciplinary applicationsEngineering, multidisciplinaryMathematics, interdisciplinary applicationsMetaheuristics; Fireflies; Chiroptera