Multi-Objective Optimization of Automotive Powerpoint Based on Adaptive Diversity Preservation Genetic Algorithm

Multi-objective optimization plays an important role in automotive power train, but there is the problem of inaccurate multi-objective optimization. The traditional ant colony algorithm cannot solve the multi-objective optimization problem in the automotive power train, and the optimization effect is not ideal. Therefore, a multi-objective optimization of automotive power train based on adaptive diversity preservation genetic algorithm is proposed, and the automobile power train is analyzed. Firstly, the evolutionary algorithm and multi-objective optimization theory is used to locate the influencing factors, and the indicators is divided according to the requirements of multi-objective optimization to reduce the interference factors in multi-objective optimization. Then, the evolutionary algorithm and multi-objective optimization theory is used to form an adaptive diversity genetic algorithm for automobile PowerPoint optimization, and the multi-objective optimization results is comprehensively analyzed. The MATLAB simulation results show that under certain evaluation criteria, the adaptive diversity preservation genetic algorithm is superior to the traditional ant colony algorithm in terms of multi-objective optimization accuracy and multi-objective optimization influencing factor time.