Optimal weight design of a gear train using particle swarm optimization and simulated annealing algorithms

The problem of minimum weight design of simple and multi-stage spur gear trains has been a subject of considerable interest, since many high-performance power transmission applications (e.g., automotive, aerospace, machine tools, etc.) require low weight. This paper presents two advanced optimization algorithms known as particle swarm optimization (PSO) and simulated annealing (SA) to find the optimal combination of design parameters for minimum weight of a spur gear train. The results of the proposed algorithms are compared with the previously published results. It is observed that the proposed algorithms offer better gear design solutions.