Optimization of Spur Gear Using Spider Monkey Optimization Technique

Abstract

In this paper, the optimization of the spur gear for center distance is done which reduces the weight of gear, material cost and inertial load. The design variables used are module and a minimum number of teeth on the pinion with design constraints as bending stress, the minimum number of teeth on pinion and beam strength. Spider monkey optimization technique is used to optimize the center distance of the spur gear pair. The results of SMO are compared with the classical method of computation. Spider monkey optimization (SMO) is a population-based algorithm which depicts the fission–fusion behavior of spider monkeys. The food source of spider monkey represents the near-optimal solution of a real-world problem. SMO is gaining popularity among researchers because of its ability to solve nonlinear, complex, NP-hard problems efficiently and effectively which cannot be solved by the traditional method of optimization. SMO is able to solve the stagnation and premature convergence problem in an efficient manner. Unlike other nature-inspired algorithms like genetic algorithm (GA), particle swarm optimization (PSO) and artificial bee colony (ABC) algorithm, SMO is good in making a balance between the exploitation and exploration of search space by refining the search space iteratively to find the near-optimal solution of a problem. The results show that the center distance of the spur gear pair is minimum in case of SMO than the conventional method of computation.