A Novel Fuzzy-based Traveling Salesman Approach for Emergency Routing under Disaster Scenario

Governments can face significant financial and human losses during natural disasters such as earthquakes, floods, and hurricanes. These unpredictable events trigger emergencies that cause damage to infrastructure. In order to aid victims and minimize negative impacts, it is crucial to have efficient logistical efforts to transport supplies and equipment. However, optimizing logistics during disasters is challenging, as traditional techniques like the Travelling Salesman Problem (TSP) require solving complex optimization problems. Researchers are exploring alternative solutions to overcome this challenge to quickly identify the best possible solution. The TSP is a well-known optimization problem where a salesman needs to visit a set of cities and return to the starting city, minimizing the total distance traveled. In the context of emergency routing during a Turkey earthquake, the goal is to efficiently allocate emergency resources and plan routes for emergency responders to reach affected areas. Hexagonal fuzzy numbers (HFNs) can be used to represent uncertain information, such as the severity of damage or the availability of resources in different areas affected by the earthquake. By incorporating fuzzy numbers into the TSP model, we can account for the uncertainty and make more informed decisions in emergency routing. This approach can help minimize response time, allocate resources effectively, and ensure that emergency responders reach affected areas in a timely manner. This paper focuses on addressing the symmetric TSP using HFNs in a specific scenario involving eleven earthquake-affected districts in Turkey. The problem involves utilizing geographical coordinates to determine the most efficient route for distributing emergency supplies in the region.