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天气不确定性下无人机配送的两阶段协同决策:提前取消与实时响应

王景鹏 孙萍 徐淑贤 刘鹏 蒋红光

西南交通大学学报(社会科学版)2026,Vol.27Issue(2):46-60,15.
西南交通大学学报(社会科学版)2026,Vol.27Issue(2):46-60,15.

天气不确定性下无人机配送的两阶段协同决策:提前取消与实时响应

Two-Stage Coordinated Decision-Making for UAV Delivery Under Weather Uncertainty:Pre-Cancellation and Real-Time Adaptation

王景鹏 1孙萍 1徐淑贤 2刘鹏 3蒋红光4

作者信息

  • 1. 山东大学管理学院
  • 2. 天津大学管理与经济学部
  • 3. 北京航空航天大学经济管理学院
  • 4. 山东大学齐鲁交通学院
  • 折叠

摘要

Abstract

To address the challenges of unmanned aerial vehicle(UAV)delivery under weather disturbances,such as high susceptibility to interruptions,high cancellation costs,and reduced service reliability,this paper develops a decision-making optimization framework that supports both pre-cancellation in the planning stage and real-time cancellation during the execution stage.The framework aims to minimize total operating costs and enhance system resilience under uncertain weather environments.A two-stage stochastic programming model is established,incorporating key operational constraints such as UAV endurance,payload capacity,and multi-depot coordination.To solve large-scale stochastic vehicle routing problems,this paper designs a Heuristic Column Generation(HCG)algorithm,employs a Copula-based scenario generation method to capture the correlation between depot closures and customer inaccessibility caused by weather,and validates the effectiveness of the proposed model and algorithm through extensive numerical experiments.The results show that HCG maintains solution quality within 1%of exact benchmarks across all test instances while reducing computational time by two orders of magnitude,demonstrating strong scalability.Introducing proactive pre-cancellation significantly reduces real-time failure costs during the execution stage,and improves system resilience and service reliability,especially under high demand or capacity constraints.The interaction among capacity thresholds,endurance limits,and correlated weather disturbances explains the non-monotonic cost patterns observed in large-scale instances.Accordingly,operators should adopt a dual risk control mechanism of"proactive defense-dynamic stop-loss"and allocate resources based on weather correlation characteristics to achieve an optimal balance between cost efficiency and service reliability under uncertainty.

关键词

无人机物流/天气不确定性/两阶段随机规划/提前取消/车辆路径

Key words

UAV logistics/weather uncertainty/two-stage stochastic programming/pre-cancellation/vehicle routing

引用本文复制引用

王景鹏,孙萍,徐淑贤,刘鹏,蒋红光..天气不确定性下无人机配送的两阶段协同决策:提前取消与实时响应[J].西南交通大学学报(社会科学版),2026,27(2):46-60,15.

基金项目

国家自然科学基金专项项目"低空经济商业模式构建与管理政策设计"(72542017) (72542017)

深圳市科技重大专项课题"多层级航路网络空间冲突优化技术"(KJZD20240903103806009) (KJZD20240903103806009)

山东省自然科学基金项目"数据驱动的医院预约挂号系统放号策略建模与分析"(ZR2024MG037) (ZR2024MG037)

西南交通大学学报(社会科学版)

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