# Simulation-Assisted Optimization for Large-Scale Evacuation Planning with Congestion-Dependent Delays

arXiv: https://arxiv.org/abs/2209.01535 · HTML: https://mlsanity.com/paper/2209.01535/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 56 references that are in the map.
- First posted on arXiv 4 Sep 2022.

## Builds on (most cited first, 4 of 4)

- [Simulation optimization: A review of algorithms and applications](https://mlsanity.com/paper/1706.08591/) (2017)
- [Challenges of Human-Aware AI Systems](https://mlsanity.com/paper/1910.07089/) (2019)
- [New Hardness Results for Routing on Disjoint Paths](https://mlsanity.com/paper/1611.05429/) (2016)
- [Non-approximability and Polylogarithmic Approximations of the Single-Sink Unsplittable and Confluent Dynamic Flow Problems](https://mlsanity.com/paper/1709.10307/) (2017)

## Built on by (most cited first, 2 of 2)

- [Quantum Artificial Intelligence for Mission-Critical Systems: Foundations, Architectural Elements, and Future Directions](https://mlsanity.com/paper/2511.09884/) (2025)
- [Evaluating Few-Shot Temporal Reasoning of LLMs for Human Activity Prediction in Smart Environments](https://mlsanity.com/paper/2602.11176/) (2026)

## Abstract (arXiv)

Evacuation planning is a crucial part of disaster management. However, joint optimization of its two essential components, routing and scheduling, with objectives such as minimizing average evacuation time or evacuation completion time, is a computationally hard problem. To approach it, we present MIP-LNS, a scalable optimization method that utilizes heuristic search with mathematical optimization and can optimize a variety of objective functions. We also present the method MIP-LNS-SIM, where we combine agent-based simulation with MIP-LNS to estimate delays due to congestion, as well as, find optimized plans considering such delays. We use Harris County in Houston, Texas, as our study area. We show that, within a given time limit, MIP-LNS finds better solutions than existing methods in terms of three different metrics. However, when congestion dependent delay is considered, MIP-LNS-SIM outperforms MIP-LNS in multiple performance metrics. In addition, MIP-LNS-SIM has a significantly lower percent error in estimated evacuation completion time compared to MIP-LNS.