Immune Optimization Design of Diesel Engine Valve Spring Based on the Artificial Fish Swarm

Abstract

In order to improve the reliability of the structure design of the diesel engine valve spring and its working performance, an artificial fish swarm-based immune genetic algorithm (AFS-IGA) is proposed. After the mutation operation of the immune genetic algorithm (IGA), the train operator and foraging operator of the artificial fish algorithm are added to improve the convergence speed and strengthen the optimal performance of the basic immune genetic algorithm. Compared with genetic algorithm (GA) and the IGA, the function testing results show that the convergence speed of the AFS-IGA is faster, the optimization ability of the AFS-IGA is stronger, and the optimization precision is higher. Furthermore, the optimization design results of the diesel engine valve spring show that the optimization performance of the proposed algorithm is optimal, which verifies the robustness of the AFS-IGA.