Facility Location and Emergency Management
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The key innovation is to turn limiting queueing behavior as call arrival rates approach zero into explicit approximations for performance losses associated with calls that have to wait, enabling mixed-integer linear programming formulations with theoretical guarantees on solution quality in the light-traffic regime.
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Light-Traffic Asymptotics for Emergency Service Planning Timely emergency response depends on where rescue teams are stationed and which areas they serve—decisions that shape response times and uncertainty in each team’s service durations and availability. In “Location-Allocation of Emergency Service Systems in Light Traffic,” Xin Wang, Weiliang Liu, Loon Ching Tang, and Zhisheng Ye use light-traffic asymptotics to explicitly capture these decision-dependent effects in tractable queueing-based location-allocation optimization models. The key innovation is to turn limiting queueing behavior as call arrival rates approach zero into explicit approximations for performance losses associated with calls that have to wait. These approximations connect queueing performance to planning decisions, enabling mixed-integer linear programming formulations with theoretical guarantees on solution quality in the light-traffic regime. In simulations using Singapore lift-trap rescue data, the optimized plans reduced projected annual late rescues by about 70% relative to the existing arrangement.
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@article{Wang2026Location,
title = {Location-Allocation of Emergency Service Systems in Light Traffic},
author = {X.R. Wang and Weiliang Liu and Loon Ching Tang and Zhi‐Sheng Ye},
journal = {Operations Research},
year = {2026},
doi = {10.1287/opre.2024.1272},
url = {https://doi.org/10.1287/opre.2024.1272}
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