Location optimization for evacuation signs and cellular automaton model simulation for evacuation in smoke

The present article studies the method of locating evacuation signs in a room full of smoke and a two steps optimization algorithm is proposed to obtain the best locations of evacuation signs in a building room. The efficiency of signs is validated by evacuation simulation with a cellular automaton (CA) model. The problem of signs location is divided into two optimization problems: maximal covering location problem and P-center problem, which are foundational problems in facility location problems. Maximal covering location problem is solved with Greedy Adding algorithm to obtain the initial locations of evacuation signs, which is not necessarily the best result. P-center problem is solved with an enumeration-like algorithm to obtain the final locations of all signs. The result of optimization shows pedestrians in a room full of smoke can find the shortest path to exit with the guidance of evacuation signs, so the evacuation time is shortest and people are safest.