【摘要】 针对电动汽车路径规划问题,创新性提出一种改进飞蛾算法进行求解.首先考虑道路拥挤性,将电池能耗作为约束条件,建立行驶总时间最小的电动汽车路径优化模型;其次采用改进飞蛾算法进行求解,引入自适应权重因子,改变飞蛾位置更新方式,有效平衡局部与全局的开掘能力;将火焰数量减少机制由直线变为曲线下降,加快收敛速度;设计变螺旋位置更新机制,动态调整螺旋线形状,提高全局开发能力;融合模拟退火和柯西变异策略,增强算法抗局部极值能力.最后由基准函数测试和算例应用结果表明,改进飞蛾算法寻优能力更强,能够有效地求解电动汽车路径优化问题.更多还原

【Abstract】 An improved moth algorithm is proposed to solve the path planning problem of electric vehicles.Firstly, the road congestion is considered and the battery energy consumption is taken as the constraint condition to establish the path optimization model of electric vehicles with the minimum driving time.Secondly, the improved moth algorithm was used to solved the problem, and the adaptive weight factor is introduced to change the position updating mode of the moth to effectively balance the local and global digging ability.The mechanism of flame quantity reduction is changed from straight line to declining curve to accelerate the convergence speed.A variable helix position updating mechanism is designed and the helix shape is dynamically adjusted to improve the global development ability.The simulated annealing and Cauchy mutation strategies are combined to enhance the anti-local extremum capability of the algorithm.Finally, the test results of the reference function and the application of the example show that the improved moth algorithm has stronger optimization ability and can effectively solve the path optimization problem of electric vehicles.更多还原