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A Conflict-Based Path-Generation Heuristic for Evacuation Planning

Artificial Intelligence 2013-09-12 v1 Optimization and Control

Abstract

Evacuation planning and scheduling is a critical aspect of disaster management and national security applications. This paper proposes a conflict-based path-generation approach for evacuation planning. Its key idea is to generate evacuation routes lazily for evacuated areas and to optimize the evacuation over these routes in a master problem. Each new path is generated to remedy conflicts in the evacuation and adds new columns and a new row in the master problem. The algorithm is applied to massive flood scenarios in the Hawkesbury-Nepean river (West Sydney, Australia) which require evacuating in the order of 70,000 persons. The proposed approach reduces the number of variables from 4,500,000 in a Mixed Integer Programming (MIP) formulation to 30,000 in the case study. With this approach, realistic evacuations scenarios can be solved near-optimally in real time, supporting both evacuation planning in strategic, tactical, and operational environments.

Keywords

Cite

@article{arxiv.1309.2693,
  title  = {A Conflict-Based Path-Generation Heuristic for Evacuation Planning},
  author = {Victor Pillac and Pascal Van Henetenryck and Caroline Even},
  journal= {arXiv preprint arXiv:1309.2693},
  year   = {2013}
}

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Technical report

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