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

Abstract

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

CLC Number:

O221.2

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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URL: https://www.ort.shu.edu.cn/EN/10.15960/j.cnki.issn.1007-6093.2026.03.012

https://www.ort.shu.edu.cn/EN/Y2026/V30/I3/204

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

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