Simulation-based multi-objective optimization for enhanced safety of fire emergency response in metro stations

Abstract

This study establishes a multi-objective optimization (MOO) model for fire emergency response in the metro station using a simulation-based analysis, in which the emergency response time and the number of firefighters are both minimized. A Hierarchical Timed Color Petri Nets (HTCPN) model is constructed to simulate different scenarios. The Skyline operator is adopted to solve the MOO problem based on the simulated dataset. Eventually, a case study of fire emergency response at the Simenkou metro station in Wuhan is conducted to verify the feasibility of the proposed approach. The case study implies that: (1) The constructed HTCPN model is correct, reasonable, and effective; (2) Compared to the baselines, simulation-based MOO can reduce the number of assigned firefighters and the emergency response time by 38.7% and 31.4%, respectively; (3) After considering the interaction between the firefighting and rescue teams, the average improvement of all scenarios can be further improved. The novelty of this research lies in that: (a) Through Petri nets combined with the emergency response process of metro stations, an HTCPN model is constructed, which appropriately represents the relationship between the relevant parts; (b) The optimal emergency response strategy is given from an MOO perspective based on the simulated dataset, which considers the response time and allocation of firefighters simultaneously.