With more and more terror attacks in France, we established a model to plan routes for tourist evacuation and emergency personnel to enter the Louvre. This model allows tourists to evacuate the Louvre more quickly and safely while emergency personnel can reach all parts of the Louvre as soon as possible. We find out the "exits" that each visitor can reach in the shortest time through Ant Colony Optimization, and divide the area of the same "exits" tourists chose. According to the number of elevators chosen by tourists, the elevator with the least number is selected for emergency personnel. At the same time, by choosing the number of exits, we can determine whether the route is an exit to ground floor or to B2. Then, Poisson distribution calculation based on the probability of a visitor arriving at an elevator, and the waiting time of each elevator is calculated by Queuing Theory. Secondly, we use Logistic Model to simulate the population density growth of these two layers. Then, using population density distribution at each moment to help visitors choose the fastest exit.

Hongzhi Wang, Chenyang Wen, Yifeng Guo, Yangyang Zhou and Ming Zhu. Emergency Escape Route Planning for the Louvre Summary. Academic Journal of Computing & Information Science (2019), Vol. 2, Issue 2: 78-84. https://doi.org/10.25236/AJCIS.010041.

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