摘要
针对航空物流配送中的运输路径优化问题,提出了一种基于改进蚁群算法的航空物流配送路径智能优化方法。针对传统蚁群算法存在收敛速度慢、容易限于局部最优的不足,采用了改进的信息启发因子和信息素浓度更新策略,并将其应用于航空物流配送路径优化问题的求解。通过仿真分析表明,所提改进蚁群算法能够打破局部最优,具有更快的收敛速度,且该航空物流配送路径优化方法兼顾了运输时间和成本,能够有效节省各项开销,更加符合实际情况。
Regarding the transportation route optimization in aviation logistics distribution problem,this paper proposes an intelligent optimization method for aviation logistics distribution path based on improved Ant Colony Optimization.This paper adopts an improved information heuristic factor and pheromone concentration update strategy,and consider the disadvantages of slow convergence speed and easy to be limited to local optimal existing in the traditional one,and applies it to the solution of the optimization problem of aviation logistics distribution route,The simulation analysis shows that the improved Ant Colony Optimization proposed in the article can break the local optimum and has a faster convergence speed,and the air logistics distribution route optimization method takes into account transportation time and cost,and can effectively save various expenses.The path optimization scheme is more in line with the actual situation.
作者
王玙
WANG Yu(Xi’an Vocational and Technical College of Aeronautics and Astronautics,Xi’an 710089,China)
出处
《信息技术》
2021年第11期76-80,共5页
Information Technology
基金
陕西省教改课题(19GY011)
中国职业技术教育学会2021年职业教育重点课题(SZ21B035)。
关键词
蚁群算法
航空物流
路径优化
运输成本
收敛速度
Ant Colony Optimization
aviation logistics
path optimization
transportation cost
convergence speed
