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 minim...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.展开更多
文摘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.
