Data Sheet 1_Maritime search and rescue resource location–allocation–scheduling under uncertain demand and time-varying locations.pdf

Unlike conventional emergency logistics, maritime incidents are not only stochastic but also involve demand locations that evolve over time under ocean environmental influences. To address these characteristics, we develop a two-stage dynamic location–allocation–scheduling (2S-DLAS) model for maritime SAR operations under uncertain demand and time-varying demand locations.

The model minimizes total rescue cost by jointly optimizing rescue base locations, the allocation of multiple SAR resource types, and the coordinated routing and task assignment of SAR platforms. It explicitly captures the dynamic coupling between travel time and ocean conditions and incorporates navigational restrictions into accessibility constraints. To solve the model, we use a Sample Average Approximation (SAA) framework and design an Improved Adaptive Large Neighborhood Search (IALNS) algorithm that integrates cross-stage nested neighborhoods to improve solution quality and computational efficiency.