A multi-objective route planning model based on genetic algorithm for cuboid surfaces. (2nd January 2018)

• Record Type: Journal Article
• Authors: Ozmen Koca, Gonca; Dogan, Sengul; Yilmaz, Hicran
• Is Part Of: Automatika. Volume 59:Number 1(2018)
• Page Start: 120
• Page End: 130
• Publication Date: 2018-01-02
• Subjects: Route planning -- optimisation -- genetic algorithm -- travelling salesman problem; Automatic control -- Periodicals; 629.805
• DOI: 10.1080/00051144.2018.1498205
• Languages: English
• ISSNs: 0005-1144

Abstract

ABSTRACT: During a natural disaster, risk management for the evacuation of people in high-rise buildings is very important for saving lives. In the case of fire, all parameters such as detection, lighting, warning systems, etc. for safety must be used interactively. Determination of evacuation conditions and different ways out are important parameters during the fire. In this study, a system is proposed for evacuating people from building with the shortest/safest route, taking into account certain factors to evaluate the current situation of the fire. Travelling Salesman Problem (TSP) may be adapted to this real-life problem to protect people in the shortest time finding optimum route. In this study, the system based on Genetic Algorithm is performed using the online information about smoke, heat and safety level, the location of fire and the potential congestion of people in order to evacuate people from the building with safety route. The system contains two- and three-dimensional surface applications to ensure evacuation with optimum distance inside/outside of the building. Results are evaluated considering the evacuation distance. Compared to other methods in the literature, the solution to this problem is improved by adding the evacuation process for the elevator and inside of the building.