Aliya, Tasya Putri (2025) Optimasi Rute Unmanned Aerial Vehicle Dalam Mencegah Penyebaran Kebakaran Semak Di Wilayah Metropolitan Perth Menggunakan Algoritma Hybrid Particle Swarm Optimization Dan Genetic Algorithm. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Kebakaran hutan sering terjadi di Australia, terutama pada musim kering dan panas, dengan dampak negatif yang signifikan terhadap ekosistem dan harta benda. Bencana ini menjadi masalah serius yang semakin parah akibat perubahan iklim. Pemerintah Australia telah mengupayakan beberapa cara untuk menanggulangi masalah ini, termasuk menyediakan sistem deteksi peringatan dini dan melakukan inspeksi menggunakan kombinasi SSA dan Radio Repeater. Namun, solusi ini tidak dapat mencegah penyebaran api. Oleh karena itu, kombinasi UAS PD-2 VTOL dan UAV Aerones diusulkan untuk meningkatkan efektivitas inspeksi dan pencegahan penyebaran api. Dengan mengoptimalkan rute UAV menggunakan pendekatan hibrid antara Particle Swarm Optimization (PSO) dan Genetic Algorithm (GA) dalam kerangka Multi-Depot Vehicle Routing Problem (MDVRP). Penelitian ini bertujuan untuk menyelesaikan masalah penentuan rute terbaik yang dilalui UAS dalam melakukan inspeksi kebakaran semak di Wilayah Metropolitan Perth dengan menggunakan algoritma hybrid PSO dan GA, sehingga dapat mencegah penyebaran kebakaran secara lebih efektif.
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Bushfire frequently occur in Australia, especially during summer seasons, with significant negative impacts on ecosystems and property. This has become a serious problem worsen by climate change. The Australian government has made several efforts to address this issue, including providing early warning detection systems and conducting inspections using a combination of SSA and Radio Repeater. However, these solutions cannot prevent the spread of fire. Therefore, a combination of UAS PD-2 VTOL and UAV Aerones is proposed to improve the effectiveness of inspection and fire prevention. By optimizing UAV routes using the Hybrid Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) within the framework of the Multi-Depot Vehicle Routing Problem (MDVRP). This study aims to solve the problem of determining the best routes for UAS in conducting bushfire inspections in the Perth Metropolitan Area using the hybrid PSO and GA algorithm, thereby preventing the spread of fires more effectively.
| Item Type: | Thesis (Other) |
|---|---|
| Uncontrolled Keywords: | Genetic Algorithm, MDVRP, Optimasi, Particle Swarm Optimization, UAV, Genetic Algorithm, MDVRP, Optimization, Particle Swarm Optimization, UAV |
| 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: | Tasya Putri Aliya |
| Date Deposited: | 23 Jul 2025 00:49 |
| Last Modified: | 23 Jul 2025 00:49 |
| URI: | http://repository.its.ac.id/id/eprint/120746 |
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