Solving Mechanical Engineering Problems by Metaheuristic Methods

Year 2023, Volume: 2 Issue: 2, 1 - 17, 30.12.2023

Samet Panda , Serhat Kılıçarslan , Abdullah Elen

Abstract

The goal of optimization is to create the "best" design possible given a set of prioritized conditions or constraints. These include increasing productivity, power, reliability, longevity, efficiency, and utilization. Because of their simplicity and speed in finding solutions, metaheuristic algorithms, one of the optimization techniques, have grown in importance in engineering design in recent years. This has resulted in the widespread use of metaheuristics and a growing proclivity to create new algorithms. In this study, a research was conducted on addressing real-world problems (Robot Gripper Problem, Pressure Vessel Design Problem, Rolling Element Bearing Problem, Step-Cone Pulley Problem, Tension Compression Spring Design Problem, Three-Bar Truss Beam Design Problem, Weight Minimization of Speed Reducer Problem and Welded Beam Design Problem) in the field of mechanical engineering with metaheuristic algorithms (Ant Colony Optimization, Artificial Bee Colony, Salp Swarm Algorithm and Sine Cosine Algorithm) and performing performance analyzes of these algorithms. In the experimental studies, four different scenarios were progressively determined according to various number of iterations and population parameters. Consequently, it can be confidently asserted that ACOR not only produces superior solutions but also boasts an ideal running time for efficiently solving real-world problems.

Keywords

Optimization, metaheuristics, real-world problems, engineering problems

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