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What is Hybrid Optimization for Relief Logistics about?

This research presents a data-driven hybrid scenario-based robust optimization method for designing relief logistics networks, integrating machine learning to enhance disaster management under uncertainty. It addresses facility disruptions and uncertain parameters such as casualty numbers and transportation times, demonstrating its effectiveness through a case study of the Kermanshah disaster. The proposed methodology allows for efficient transportation of casualties to medical services at a fair cost, impr

Author

975045

Language

EN