Optimization for fire evacuation applying maximum flow cost algorithm to improve the time-response in underground coal mines

During an underground mine fire, the presence of smoke and toxic gasses, low visibility, and changes in the ventilation system will make it extremely difficult to identify evacuation measures and the optimum path to safety. This paper presents an algorithm for solving the maximum cost flow network problem (MCFNP) for fire evacuations considering the distribution of toxic gasses inside the mine in real-time. The proposed algorithm will identify the optimum evacuation paths requiring minimum decision-making time. The algorithm holds data in nodes and arcs accumulating values at each iteration and updating the network depending on the mine conditions. To achieve this, a fire simulation was performed in VentSimTM software to extract the air velocity, gas concentrations, visibility, and changes in the ventilation system data throughout the incident zone. The presented algorithm finds the evacuation paths improving time-response and comparing the decision-making of miners in a successful evacuation. The prediction of the concentration of toxic gasses, recommends a safety path and avoids exposure to the danger zone despite the presence of the shortest-path and road capacity toward the surface.