TITLE:
Analysis of Evacuation of Tourists Based on the Louvre’s Emergency
AUTHORS:
Rui Tang, Xiaozhen Luan, Shiwei Xu, Fuliang Lu, Wei Zhang
KEYWORDS:
NT Model, Linear Programming, Genetic Algorithm, Cellular Automata, M/G/C/C Queuing Network Model, Emergency, Evacuation
JOURNAL NAME:
Open Journal of Applied Sciences,
Vol.9 No.6,
June
30,
2019
ABSTRACT: Due to France has suffered from many terrorist attacks and the number of
visitors to the Louvre has gradually increased in recent years, a good
evacuation plan for the Louvre is of vital significance. We use the
minimization of the total evacuation time of
all tourists as the optimization goal to find an optimal path. For conventional
emergencies, a static model is built to evacuate visitors. And then we
establish a nonlinear programming model. Using Lingo software, we get the
distribution information of the visitors in different exhibition halls. For
unconventional emergencies, we establish an adaptive dynamic model of tourist
evacuation based on genetic algorithm. The sensitivity analysis of the model is
considered by adding new paths. By solving the nonlinear programming problem
with the double objective function of maximizing evacuation time and balancing
the number of people in every path,
we get the evacuation time last 1582.74 s.
Finally, according to our result, we built mathematical models for the evacuation after an emergency and analyzed how to
adapt and implement our models for other large and crowded structures.