Optimisation of gear reducer using evolutionary algorithm

When designing a gear reducer, there are many important factors to be considered, such as weight, size, strength, durability material and geometry. The material of the gear reducer has a key impact on its weight. In this paper, a two-stage gear reducer is optimised with major conflict functions like minimisation of gear material volume, minimisation of centre distance, maximisation of power and maximisation of efficiency as objectives with design stresses as the constraints. We have considered two different types of materials for this study. A new population-based evolutionary algorithm named selective breeding algorithm is considered to solve this design problem, with two different types of materials. In selective breeding algorithm, solutions are made to breed, mutate, sort and multiple better solutions are formed. Then fitness conditions are placed, best solutions are generated and results are compared with an existing design.