This special session explores how two major areas of artificial intelligence, such as evolutionary computation and machine learning, can improve natural disaster preparedness, response, and recovery and the efficiency of humanitarian logistics. In a world where natural disasters are becoming more frequent and devastating, the integration of advanced optimization and predictive approaches becomes crucial to save lives and mitigate the unforeseen impact of nature. Proposals in this session will range from optimizing resource distribution routes to accurately predicting catastrophic events, using the synergy of evolutionary optimization algorithms and the predictive capabilities of machine learning.

Topics of Interest

• Optimization of resource allocation in emergencies
• Prediction of natural disasters using deep learning and machine learning
• Evacuation planning and shelter management
• Allocation and management of limited resources
• Early response and damage mitigation warning systems
• Prediction of climate change impact and frequency of extreme weather events
• Disaster simulation and modeling systems using AI
• Optimization of air transport and drones in emergency situations
• Disease prediction and management models in emergency situations using machine learning
• Structural damage estimation and prediction in buildings after natural disasters
• Optimization of emergency communication networks
• Implementation of algorithms for coordinating rescue teams

Organisers

• Mario A. Navarro
  Universidad de Guadalajara, Mexico
  mario.navarro@academicos.udg.mx
• Diego Oliva
  Universidad de Guadalajara, Mexico
  diego.oliva@cucei.udg.mx”