Work

Multi-Objective Optimization Model for Emergency Evacuation Based on Adaptive Ant Colony Algorithm

Year: 2025

Type: article

Abstract: Evacuation in public places under emergency situations represents a significant area of management research. With the rapid development of the railway industry, the evacuation of railway stations has gradually attracted attention. This article employs the minimization of congestion degree and total evacuation time as primary objectives. In addition, the psychological behavior of individuals and the impact of congestion are sufficiently considered. Moreover, an adaptive Cauchy mutation operator is adopted for flexible population diversity. As a result, a multi-objective optimization model for the evacuation paths is established, with an improved adaptive quantum ant colony algorithm, and a comparison between the model based on adaptive quantum ant colony algorithm and the traditional ant colony model is made.

Source: AI

DOI: 10.3390/ai6090203

Authors: Jiacheng Yuan, Baiqing Sun

Institution: Harbin Institute of Technology

Language: English

Topic: Evacuation and Crowd Dynamics

Subfield: Ocean Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Sustainable cities and communities

Open Access status: gold

Estimated APC paid: $1,930