Genetic Algorithm-based Routing and Scheduling for Wildfire Suppression using a Team of UAVs

John, J and Sundaram, S (2024) Genetic Algorithm-based Routing and Scheduling for Wildfire Suppression using a Team of UAVs. In: 13th IEEE Congress on Evolutionary Computation, CEC 2024, 30 June 2024through 5 July 2024, Yokohama.

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Abstract

This paper addresses early wildfire management using a team of UAV s for the mitigation of fires. The early detection and mitigation systems help in alleviating the destruction with reduced resource utilization. A Genetic Algorithm-based Routing and Scheduling with Time constraints (GARST) is proposed to find the shortest schedule route to mitigate the fires as Single UAV Tasks (SUT). The objective of GARST is to compute the route and schedule of the UAVs so that the UAVS reach the assigned fire locations before the fire becomes a Multi UAV Task (MUT) and completely quench the fire using the extinguisher. The fitness function used for the genetic algorithm is the total quench time for mitigation of total fires. The selection, crossover, mutation operators, and elitist strategies collectively ensure the exploration and exploitation of the solution space, maintaining genetic diversity, preventing premature convergence, and preserving high-performing individuals for the effective optimization of solutions. The GARST effectively addresses the challenges posed by the NP-complete problem of routing and scheduling for growing tasks with time constraints. The GARST is able to handle infeasible scenarios effectively, contributing to the overall optimization of the wildfire management system. © 2024 IEEE.

Item Type:	Conference Paper
Publication:	2024 IEEE Congress on Evolutionary Computation, CEC 2024 - Proceedings
Publisher:	Institute of Electrical and Electronics Engineers Inc.
Additional Information:	The copyright for this article belongs to publisher.
Keywords:	Aircraft detection; Fire extinguishers; Premixed flames; Resource allocation; Scheduling algorithms; Unmanned aerial vehicles (UAV), Aerial vehicle; Early detection system; Mitigation systems; Optimisations; Routing and scheduling; Task allocation; Time constraints; Unmanned aerial vehicle; Wildfire management; Wildfire suppression, Genetic algorithms
Department/Centre:	Division of Mechanical Sciences > Aerospace Engineering(Formerly Aeronautical Engineering)
Date Deposited:	15 Sep 2024 06:06
Last Modified:	15 Sep 2024 06:06
URI:	http://eprints.iisc.ac.in/id/eprint/86083

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