Particle Swarm Optimization/Greedy-Search Algorithm for Helicopter Mission Assignment in Disaster Relief

Abstract

In the immediate aftermath of a large-scale disaster, optimal helicopter rescue mission assignment is critical to saving many lives. The current practice in the field is mostly humancentered, however. Japan Aerospace Exploration Agency has been developing a decisionsupport system for aircraft operation in order to promptly plan and execute rescue missions.The current research focuses on evacuation missions in particular and investigates the potential of particle swarm optimization (PSO) with integrated greedy search in aircraft resource management. We propose a robust particle model which can reflect various

Relief Aircraft Dispatch Strategies Based on Different Levels of Information Sharing Systems

“…Here, one flight has only one destination (one rescue shelter). It is a common dispatch method for disaster relief activities [1,35]. According to the reported injury request, the dispatchment center assigns one aircraft to one rescue shelter.…”

A survey on recent optimal techniques for securing unmanned aerial vehicles applications

“…The method is influenced by the systemic working of social insects, which reveal three desired features in multirobots: scalability, robustness, and flexibility. Swarm robotics while performing their duties can be used in various applications such as military, 72‐75 monitoring, 76,77 healthcare, 128‐131 disaster relief 132‐137 . Swarm robots could either communicate tacitly or directly 138 .…”