Optimasi Rute Unmanned Aerial Vehicles Dalam Mencegah Penyebaran Kebakaran Semak di Wilayah Metropolitan Perth Menggunakan Algoritma Discrete Firefly Algorithm

Gantari, Nabila Kumala (2025) Optimasi Rute Unmanned Aerial Vehicles Dalam Mencegah Penyebaran Kebakaran Semak di Wilayah Metropolitan Perth Menggunakan Algoritma Discrete Firefly Algorithm. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Dalam rangka mencegah penyebaran kebakaran semak di wilayah metropolitan Perth, diperlukan optimasi rute penerbangan Unmanned Aerial Vehicles (UAV) supaya bersifat efektif dan efisien. Permasalahan optimasi rute penerbangan UAV dirancang dengan model pendekatan Multi-Depot Vehicle Routing Problem (MDVRP), dilengkapi oleh beberapa truk pemadam kebakaran sebagai depot penanganan kebakaran semak. Tugas akhir ini mengajukan solusi rute penerbangan UAV yang dioptimalkan oleh algoritma metaheuristik Discrete Firefly Algorithm (DFA), yaitu Firefly Algorithm yang bersifat diskret. Penentuan depot pada tugas akhir ini didasarkan pada hasil klasterisasi data persebaran kebakaran hutan di wilayah metropolitan Perth selama dua periode kenaikan tren frekuensi kebakaran semak, terbagi dalam tiga skenario data. Hasil penentuan depot dirumuskan dalam model matematis MDVRP, diikuti oleh implementasi algoritma DFA pada data persebaran kebakaran semak. Selanjutnya, dalam proses uji coba skenario dan analisis hasil optimasi, didapatkan hasil bahwa DFA dapat menghasilkan rute yang mendekati optimal untuk ketiga skenario data. Hasil tersebut didapatkan dari komputasi DFA menggunakan kombinasi parameter jumlah iterasi, populasi, dan koefisien penyerapan cahaya terbaik. Namun, ketika dibandingkan dengan algoritma Population-Based Simulated Annealing (PSA), hasil perbandingan menunjukkan bahwa PSA memberikan solusi rute dengan jarak tempuh yang lebih efektif 0,16% dan waktu tempuh yang lebih efisien 0,20% daripada DFA. Meskipun begitu, hasil rute dari komputasi DFA diharapkan dapat mendukung upaya pencegahan penyebaran kebakaran semak di wilayah metropolitan Perth serta berdampak positif untuk lingkungan, ekonomi, dan sosial masyarakat.
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In order to prevent the spread of bushfires in the Perth metropolitan area, optimizing the flight routes of Unmanned Aerial Vehicles (UAV) is essential to ensure effective and efficient monitoring. The UAV flight route optimization problem is modeled using a Multi-Depot Vehicle Routing Problem (MDVRP) approach, incorporating several fire trucks as depots for bushfire response. This thesis proposes UAV flight route solutions optimized using the Discrete Firefly Algorithm (DFA), a discrete variant of the Firefly Algorithm. Depot determination in this study is based on the clustering results of bushfire distribution data in the Perth metropolitan area over two periods of increasing fire frequency, divided into three data scenarios. The determined depots are then formulated into the MDVRP mathematical model, followed by the implementation of the DFA on the clustered fire distribution points. Scenario testing and optimization analysis indicate that DFA is capable of generating near-optimal routes for all three data scenarios. These results were achieved using specific combinations of parameters, including the number of iterations, population size, and light absorption coefficient (gamma). However, when compared to the Population-Based Simulated Annealing (PSA) algorithm, the results show that PSA provides 0,16% more effective route distance and 0,20% more efficient UAV traveling time solutions for this case study. Nevertheless, the routes generated through DFA computation are expected to support rapid and efficient bushfire prevention efforts in the Perth metropolitan area, while also having a positive impact on environmental, economic, and social aspects of the community.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Firefly Algorithm, Kebakaran Semak, Multi-Depot Vehicle Routing Problem, Unmanned Aerial Vehicle, Bushfire, Firefly Algorithm, Multi-Depot Vehicle Routing Problem, Unmanned Aerial Vehicle
Subjects:	T Technology > T Technology (General) > T57.84 Heuristic algorithms.
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Information System > 57201-(S1) Undergraduate Thesis
Depositing User:	Nabila Kumala Gantari
Date Deposited:	28 Jul 2025 07:40
Last Modified:	28 Jul 2025 07:40
URI:	http://repository.its.ac.id/id/eprint/122622

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