Scientific paper ID 2366 : 2023/2

Branislav Milenković, Mladen Krstić

Engineering problems are some of the currently most prominent research issues. One of the classes of engineering problems are engineering design problems, where a set of variables is calibrated for the optimization function to have a minimal or maximal value. This function often considers energy efficiency, cost efficiency, production efficiency, etc., in engineering design. One of the ways in which such problems are solved is the application of metaheuristics. This paper demonstrates how the Beluga Whale Algorithm can be used to solve certain optimization problems in mechanical engineering. Firstly, a brief review of the Beluga Whale Algorithm, as well as its biological inspiration, is given along with the most important formulae. The pseudo code for this algorithm was written using the MATLAB R2022a software suite. The Beluga Whale Algorithm was used for the optimization of engineering problems, such as: 3D beam optimization, multiple-disk clutch brake and cantilever beam optimization. The results presented in this paper show that the Beluga Whale Algorithm can produce relevant results in the field of engineering design problems.

Beluga whale Algorithm Optimization EngineeringBranislav Milenković Mladen Krstić


[2] . F.Fedorik, Using optimizations algorithms by designing structures, doctoral thesis, Institute of Structural Mechanics, Faculty of Civil Engineering Brno, University of Technology, (2013), 119-140.

[3] . Dj. Jovanović, B. Milenković, M. Krstić, Application of Grasshopper Algorithm in Mechanical Engineering, YOURS, pp.1-6, 2020.

[4] . P. Sabarinath, M. R. Thansekhar, and R. Saravanan, Performance Evaluation of Particle Swarm Optimization Algorithm for optimial design of belt pulley system in Swarm, Evolutionary, and Memetic Computing, vol. 8297 of Lecture Notes in Computer Science, pp. 601–616, Springer, Cham, Switzerland, 2013.

[5] . J. L. Marcelin, Genetic Optimisation of Gear International Journal of Advanced Manufacturing Technology, vol. 17, no. 12, pp. 910–915, 2001.

[6] . Mirjalili S, The Ant Lion Optimizer, Adv Eng Software,,83:80-98, 2015.

[7] . Chickermane H, Gea H. Structural optimization using a new local approximation method, Int J Number Methods Eng, 39:829-46, 1996.

[8] . (0)-,Beluga whale optimization (BWO) algorithm is a swarm-based,phase, and whale fall phase




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