OPTIMIZATION OF CROWD EVACUATION SIMULATION IN TEACHING AND LEARNING FACILITIES
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Universiti Malaysia Sarawak
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This study explores the optimization of crowd evacuation in teaching and learning facilities at Universiti Malaysia Sarawak (UNIMAS) using Particle Swarm Optimization (PSO), investigating whether PSO can enhance evacuation efficiency by reducing evacuation times and managing congestion, particularly in high-density scenarios or when exits are blocked. A crowd evacuation simulation system was developed using MATLAB, incorporating PSO to dynamically optimize evacuation routes based on building layouts and agent densities. The study tested three exit configurations: three exits open, two exits with one blocked, and one exit with two blocked, and also included slow-moving agents to simulate individuals with reduced mobility, such as the elderly. Results show that PSO consistently reduced evacuation times compared to non-optimized scenarios, with the most significant improvements observed in the one-exit scenario for 130 agents with 10 slow-moving agents, where evacuation times were reduced from 58.28 seconds in non-PSO simulations to 26.25 seconds with PSO. In scenarios with two exits, PSO reduced evacuation time from 23.75 seconds to 12.44 seconds for 130 agents, and with three exits, it decreased evacuation times from 14.26 seconds to 6.17 seconds for 10 agents. PSO also mitigated delays caused by slow agents, improving evacuation flow even in constrained environments, thus highlighting its effectiveness in optimizing crowd evacuation strategies in educational settings and offering potential applications for campus safety and emergency preparedness.