Distributed constrained optimization for post-earthquake rescue path planning
This paper proposes a post-earthquake rescue path planning model based on Distributed Constrained Optimization Problems(DCOPs).The mathematical model is built by analyzing factors such as seismic intensity,seismic damage index and roadway reliability.Coupled with actual post-earthquake rescue maps,a novel Adaptive Local Cost Simulation-based algorithm(ALCS)is proposed to solve the model.The agent in ALCS employs a bias correction strategy to pre-correct the local cost and obtain a better solution at the initial stage.Meanwhile,an adaptive strategy is designed to improve the generalization ability of the algorithm.Our extensive experimental results on benchmark problems demonstrate the constructed DCOPs-based rescue path planning model effectively improves the efficiency of post-earthquake rescue,and the proposed ALCS algorithm outperforms the state-of-the-art local search-based DCOPs solving algorithms,and also effectively plans multiple rescue paths by solving the post-earthquake rescue path planning model.
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