Memetic Algorithms for Assessing Post-Disaster Scenarios

• Grant number: 25/01567-1
• Support Opportunities: Scholarships abroad - Research Internship - Scientific Initiation
• Start date: May 01, 2025
• End date: July 31, 2025
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Theory of Computation
• Principal Investigator: Mário César San Felice
• Grantee: Matheus de Almeida Mazieiro
• Supervisor: Pablo Alberto Moscato
• Host Institution: Centro de Ciências Exatas e de Tecnologia (CCET). Universidade Federal de São Carlos (UFSCAR). São Carlos , SP, Brazil
• Institution abroad: University of Newcastle, Australia
• Associated to the scholarship: 23/10948-3 - Hybrid Genetic Meta-Heuristics for the Traveling Salesman Problem with a Flying Sidekick, BP.IC

Abstract

Natural disasters often disrupt ground networks, posing significant challenges for humanitarian logistics when assessing communities in affected areas. To address this, the Combined Drone Orienteering Problem (CDOP) integrates the use of drones and trucks for post-disaster assessments, maximizing informational gains within a limited time frame. Drones, capable of traversing inaccessible areas, gather real-time data, while trucks serve as mobile bases for battery swaps. This project aims to develop memetic algorithms to efficiently solve the CDOP, in particular, algorithms with a ternary tree structure for its population or inspired by the Hybrid Genetic Search with Adaptive Diversity Control. The proposed method will enhance solution quality by incorporating problem-specific properties, ensuring its effectiveness in operational research and real-world disaster scenarios. The research is expected to yield state-of-the-art results, contributing to both academic knowledge and practical humanitarian efforts.