Abstract Crowd management and fire safety studies indicate that the correct prediction of the threat caused by fire is crucial behavior which could lead to survival. Incorporating intelligence into exit choice models for accomplishing evacuation simulations involving such behavior is essential. Escaping from moving source of panic such as fire is of tremendous frightening event while evacuation situation. Predicting the dynamic of fire spreading and the exit clogging are intelligent aspects which help the individuals follow the correct behaviors for their evacuation. This article proposes an intelligent approach to accomplishing typical evacuations. The agents are provided with the ability to find optimal routes that enable them overcome spreading fire. Fire and safe floor fields are proposed to provide the agents with the capability of determining intermediate points to compose optimal routes toward the effective chosen exit. The instinct human behavior of being far from the fire to protect himself from sudden unexpected attack is introduced as essential factor risen in emergency situation. Simulations are conducted in order to examine the simulated evacuees’ behavior regarding overtaking the fire and to test the efficiency of making smart and effective decisions during emergency evacuation scenarios.

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[30] Zhu J., Li W., Li H., Wu Q., and Zhang L., “A Novel Swarm Intelligence Algorithm for the Evacuation Routing Optimization Problem,” The International Arab Journal of Information Technology, vol. 14, no. 6, pp. 880-889, 2017. Mohammed Shuaib received Ph.D. Degree in Applied Mathematics, Universiti Sains Malaysia, in 2011. Field: Applied Mathematics; Mathematical Modeling; M. Sc. Degree in Mathematics, University of Jordan, in 2003; B.A. Degree in Educational sciences/ field teacher (Mathematics), University of Jordan, in 1999. From 2011 to 2018, he had been an Assistant Professor of mathematics at the Department of Computer Sciences, College of Shari’a and Islamic Studies in Al Ahsaa, Imam Mohammad Ibn Saud Islamic University (IMSIU). Currently, he is working as an Associate Professor in the same university. His current interests include modeling and simulation of crowd dynamics. His current research is about developing a crowd simulation to present the real aspects of the Hajj Crowd. Zarita Zainuddin received the B. S. degree in Mathematics from Monmouth College, USA in 1979, M. Sc. in Applied Mathematics from Ohio University, USA in 1981, M. Sc. in Mathematics (Control Theory) from UMIST, UK in 1986 and Ph.D from Universiti Sains Malaysia in 2001. She is currently a Professor at the School of Mathematical Sciences, Universiti Sains Malaysia, Penang, Malaysia. Her current interests include neural networks, image processing, bioinformatics and crowd dynamics. She focuses on the improvement and development of neural network learning algorithms involving incorporation of acceleration and optimization methods into the training of neural networks for improved accuracy and convergence.