Computational intelligence approach for multiagent coordination in emergency management of technological accidents

Abstract

This thesis explores the application of Computational Intelligence techniques in improving emergency response during technological disasters. It introduces a coordinated decision-making system based on CI techniques, including the Improved Genetic Algorithm (IGA), Improved Multi-Objective Particle Swarm Optimization (IMOPSO), and Dynamically Adjusted Multi-Objective Water Wave Optimization (DAMOWWO), which significantly enhance emergency management system performance by applying the coordination mechanisms to the agents. Comparative analysis revealed that IGA and DAMOWWO outperformed state-of-the-art algorithms by 22.3% and 20.84%, respectively. IMOPSO demonstrated a 18.12%, improvement. These findings underscore the remarkable effectiveness of these approaches in orchestrating task assignments, particularly in scenarios characterized by low and high-severity emergencies. Consequently, this study emphasizes the paramount importance of harnessing the potential of CI techniques to expedite and enhance the efficiency of disaster response efforts.