Open AccessDesign of Emergency Evacuation Scheme for Louvre
Author(s) -
Zhuoqun Zhang,
Chen Wang,
Yinzhe Wang
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/914/1/012025
Subject(s) - node (physics) , computer science , iterated function , segmentation , set (abstract data type) , graph , plan (archaeology) , algorithm , genetic algorithm , floor plan , sequence (biology) , dynamic programming , mathematical optimization , artificial intelligence , theoretical computer science , mathematics , engineering drawing , engineering , machine learning , mathematical analysis , genetics , structural engineering , archaeology , biology , history , programming language
In this paper, we used four steps in analyzing the optimal model of evacuation within the Louvre. For step 1, we refer to the traffic concept in the Dynamic Network Flow Model to define the export throughput. For step 2, considering that the original floor plan is segmented with pixel points as a unit with high complexity and little meaning, we simplify the floor plan when the model is guaranteed to be true. For step 3, we first mark the exit node, make its dual graph, and draw the point chain containing the exit node, which can divide the original image into several pieces according to the area. Breadth-First Search from each egress node can mark themselves with color, ownership and other information. For Step 4, in order to get the optimal segmentation which satisfies the definition of reasonable segmentation edge set, we use Genetic Algorithm to solve the optimization problem. A sequence consisting of the sequence numbers in the set of Edge-Cut is encoded as a gene in the Genetic Algorithm and iterated by the Theory of Chromosome Cross-Variation to obtain an optimal solution. Finally, we have designed a scientific and complete emergency evacuation plan.