摘要
为提高农村客货邮的调度效率,本文提出了一种基于星鸦优化算法(NOA)的多目标协同调度模型。该模型融合了运输成本、服务时效及资源利用率等因素,同时引入动态权重调整与高斯变异策略来提升算法性能。在湖南某农村地区开展的客货邮协同调度仿真测试结果显示,相较于对比算法中综合表现次优的改进蚁群算法,改进NOA的运输成本降低了约16.1%,服务时间缩短了约18.2%,资源利用率提高了约8.9%。
To improve the scheduling efficiency of rural passenger-freight-post services,this paper proposes a multi-objective coordinated scheduling model based on the Nutcracker Optimization Algorithm(NOA).The model integrates transportation cost,service timeliness,and resource utilization,while introducing dynamic weight adjustment and Gaussian mutation strategies to enhance algorithmic performance.The simulation experiments conducted in a rural area of Hunan Province demonstrate that,compared with the Improved Ant Colony Algorithm,the scond-best performing algorithm among the benchmarbs,the improved NOA reduces transportation cost by approximately 16.1%,shortens service time by approximately 18.2%,and increases resource utilization by approximately 8.9%.
作者
杨文欣
黄政祥
钟志康
侯漾
杨廷
刘丹
YANG Wenxin;HUANG Zhengxiang;ZHONG Zhikang;HOU Yang;YANG Ting;LIU Dan(Changsha CRRC Intelligent Control and New Energy Technology Co.,Ltd.,Changsha 410083,China;CRRC Electric Vehicle Co.,Ltd.,Zhuzhou 412007,China)
出处
《客车技术与研究》
2026年第2期38-43,共6页
Bus & Coach Technology and Research
关键词
农村客货邮
智能调度
NOA
多目标优化
动态权重分配
rural passenger-freight-post
intelligent scheduling
NOA
multi-objective optimization
dynamic weight assignment
