基于目标鲁棒性优化的两阶段无人机设施选址与调度

doi:10.15960/j.cnki.issn.1007-6093.2026.03.012

摘要/Abstract

摘要： 本文聚焦不确定需求下的无人机设施选址和应急物资调度问题,提出一种基于目标鲁棒优化的两阶段选址-调度模型。其中第一阶段决策包括设施选址、无人机分配以及应急物资的储备;第二阶段则根据实际需求实现物资调度。模型采用Wasserstein距离刻画需求分布的不确定性,结合对偶理论和仿射决策规则将问题重构为自适应鲁棒优化模型,并运用求解器对模型进行求解。数值结果表明,相较于随机规划和分布鲁棒优化模型,所提模型在设施选址与库存预置决策方面更具鲁棒性,能够有效降低灾后的应急运输成本。

关键词: 无人机运输, 设施选址, 调度, 分布鲁棒优化, 目标鲁棒性优化

Abstract: This paper focuses on the drone facility location and scheduling problem under uncertain demand, and proposes a two-stage location-scheduling model based on robust satisficing. The first-stage decisions cover facility siting, drone allocation, and emergency supply stockpiling. The second-stage operations implement supply dispatching per actual demand. The model employs the Wasserstein distance to characterize demand distribution uncertainty, reconstructs the problem into a solvable adaptive robust optimization model via duality theory and affine decision rules, and solves it using a solver. Numerical results demonstrate that, compared with stochastic programming and distributionally robust optimization models, the proposed model offers stronger robustness in facility location and inventory pre-positioning, and effectively cuts post-disaster emergency transportation costs.

Key words: drone transportation, facility location, scheduling, distributionally robust optimization, robust satisficing

中图分类号:

O221.2

过燕晶, 高盼, 吴中明. 基于目标鲁棒性优化的两阶段无人机设施选址与调度[J]. 运筹学学报（中英文）, 2026, 30(3): 204-218.

GUO Yanjing, GAO Pan, WU Zhongming. Two-stage drone facility location and scheduling based on robust satisficing[J]. Operations Research Transactions, 2026, 30(3): 204-218.

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基于目标鲁棒性优化的两阶段无人机设施选址与调度

Two-stage drone facility location and scheduling based on robust satisficing

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