Liu, Bingqing (University of California, Los Angeles), Ma, Haoxuan (University of California, Los Angeles), Ma, Jiaqi (University of California, Los Angeles)

Multi-Period Truck Scheduling with Queueing for Post-Disaster Debris Removal: A Case Study of the 2025 Los Angeles Wildfires

Scheduled for presentation during the Video Session "On-Demand Video Presentations" (VP-VP), Saturday, November 22, 2025, 08:00−18:00, On-Demand Platform

2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC), November 18-21, 2025, Gold Coast, Australia

This information is tentative and subject to change. Compiled on April 2, 2026

Abstract

Disasters such as wildfires, earthquakes, hurricanes, and floods have long posed severe threats to communities worldwide, generating massive amounts of debris. Existing truck scheduling models often minimize time cost or maximize profit, failing to accommodate updating demand and chaotic environment after major disasters and secondary hazards. This study proposes the Multi-Period Truck Scheduling problem for Debris Removal after major disasters with explicit queue modeling (MPTS-DR). The model minimizes the remaining debris periodically to minimize secondary hazards and accommodate updating demand due to ongoing cleaning and sorting. Queues at disposal sites are explicitly modeled to absorb demand surges and smooth operational uncertainty. A solution heuristic is proposed and applied to the removal of 2025 LA wildfire debris in Palisades and Eaton. Optimal fleet size and sufficient queue length are identified. Results show that it takes more than 700 days to remove all debris with workday opening hours, and around 260 days to remove with 24-hour operations.