基于遗传算法的汽车认证测试路径规划优化方法  

Optimization Method for Path Planning of Automobile Certification Test Based on Genetic Algorithm

作　　者：汪恒 Wang Heng(School of Computer and Electronic Information Engineering,Wuhan City Polytechnic,Wuhan 430064,Hubei)

机构地区：[1]武汉城市职业学院计算机与电子信息工程学院,湖北武汉430064

出　　处：《武汉工程职业技术学院学报》2025年第1期48-51,共4页Journal of Wuhan Engineering Institute

摘　　要：在汽车工业中,新车型的上市前检验是一个至关重要的环节,直接关系到车辆的安全性和性能表现。为了确保新车型能够满足严格的行业标准,在上市前需要通过一系列复杂的检验认证。这些检验通常包括多个测试项目,分布在测试场的各个角落。文中提出一种基于遗传算法的优化方法,旨在提高检验流程的效率,能够为新车型提供一个最便捷高效的测试项目顺序,从而显著减少检验过程中的时间和资源消耗。研究结果表明,基于遗传算法的路径规划较比人工测试数据,路径长度降低达到10.75%。这种方法不仅确保新车型在上市前能够接受全面而高效的检验,更有助于降低企业的运营成本,提升检验工作的整体效率和质量。通过这一创新的优化策略,汽车制造商能够更快地将新车型推向市场,同时确保消费者的安全和满意度。In the automotive industry,pre-launch testing of new vehicle models is a crucial step as it is directly related to the safety and performance of the vehicles.To insure that the new vehicle strictly meet industry standards,a serious of tests needs to be taken before it’s launch even though the tests include multiple items located throughout the testing grounds.The study proposes an optimization method based on genetic algorithms,aiming to improve the efficiency of the inspection process by providing the most convenient and efficient sequence of test items for new vehicle models,thereby significantly reducing the time and resource consumption during the inspection process.The research results show that the path planning based on genetic algorithms reduces the path length by up to 10.75%compared to manually tested data.This method not only ensures that new vehicle models receive comprehensive and efficient inspections before being launched,but also helps to reduce the operating costs of enterprises,and improves the overall efficiency and quality of the inspection work.With this innovative optimization strategy,automobile manufacturers can bring new vehicle models to the market more quickly while ensuring consumer safety and satisfaction.

关 键 词：遗传算法 车辆测试 最优路径 

分 类 号：TP319[自动化与计算机技术—计算机软件与理论]