A new Hybrid Metaheuristic Algorithm based Human Approach for Mechanical Engineering Problems

This research work develops a novel hybrid optimization algorithm called Technical and Vocational Education and Training based Particle Swarm Optimization (TVETPSO), which incorporates Technical and Vocational Education and Training (TVET) inspired human learning approach in combination with Particle Swarm Optimization (PSO) leveraging several mechanisms features as well as involving further learning phases in the proposed TVETPSO, which permit a knowledge transferring and historical generations stored. This human inspired approach allow TVETPSO algorithm to refine its exploration strategies, improve exploitation of the solutions and avoid premature convergence. Where is validated by a diverse set of Benchmark functions and measured in Design Problems such as Welded beam, Gear Train and Tension/Compression Spring. This experiments show an effective behavior against the comparative analysis of the proposed TVETPSO for solving engineering design problems. Ultimately this study offers a robust means for refining an effective resolution of real world optimization problems.