Arifuddin, Akhdan (2025) Perbandingan Algoritma Hibrida CGTO TS LS, NSGA-II, dan GWO untuk Optimasi Capacitated Vehicle Routing Problem dengan Strategi Cluster-First Route-Second. Masters thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Capacitated Vehicle Routing Problem (CVRP) merupakan tantangan utama dalam logistik yang menuntut efisiensi pelayanan pelanggan dengan tetap memperhatikan batas kapasitas kendaraan. Penelitian ini membandingkan algoritma hibrida CGTO TS LS, yang menggabungkan pendekatan Cluster-First Route-Second dengan Gorilla Troops Optimizer (GTO), Iterated Local Search (ILS), dan Advanced Tabu Search (ATS), terhadap dua algoritma metaheuristik populer, yaitu Non Dominated Sorting Genetic Algorithm (NSGA-II) dan Grey Wolf Optimizer (GWO). Evaluasi dilakukan pada dataset sintetis serta tiga dataset dunia nyata, termasuk kasus distribusi air mineral, distribusi di Belgia, dan distribusi perusahaan pupuk terbesar di Indonesia. CGTO TS LS menghasilkan total jarak tempuh terpendek sebesar 1757,57 km pada kasus distribusi air mineral, lebih baik dibandingkan NSGA-II (2230,59 km) dan GWO (4672,76 km), dengan peningkatan efisiensi masing-masing sebesar 21,2% dan 62,4%. Pada kasus distribusi pupuk bulan September, CGTO TS LS juga unggul dengan waktu eksekusi tercepat (317 detik) dibandingkan NSGA-II (371 detik) dan GWO (444 detik). Meskipun pada beberapa kasus CGTO TS LS tidak menghasilkan solusi dengan jarak terpendek, ia tetap menunjukkan keseimbangan antara efisiensi waktu dan kualitas solusi. Kemampuannya mencapai hasil stabil dalam jumlah iterasi yang terbatas menunjukkan potensi tinggi untuk diterapkan dalam skenario distribusi logistik nyata.
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The Capacitated Vehicle Routing Problem (CVRP) is a key logistics challenge that requires efficient customer service while considering vehicle capacity constraints. This study compares a hybrid algorithm, CGTO TS LS, which combines the Cluster-First Route-Second approach with Gorilla Troops Optimizer (GTO), Iterated Local Search (ILS), and Advanced Tabu Search (ATS), against two well-known metaheuristics: Non Dominated Sorting Genetic Algorithm II (NSGA-II) and Grey Wolf Optimizer (GWO). Experiments were conducted on synthetic datasets and three real-world case studies, including bottled water distribution, Belgium distribution, and a fertilizer delivery network in Indonesia. CGTO TS LS achieved the shortest total distance of 1757.57 km in the bottled water case, outperforming NSGA-II (2230.59 km) and GWO (4672.76 km), with respective improvements of 21.2% and 62.4%. In the September fertilizer dataset, CGTO TS LS also had the fastest execution time (317 seconds) compared to NSGA-II (371 seconds) and GWO (444 seconds). Although CGTO TS LS did not always produce the shortest routes in all scenarios, it consistently balanced execution time and solution quality. Its ability to achieve stable results in limited iterations demonstrates strong potential for practical use in real-world logistics optimization.
| Item Type: | Thesis (Masters) |
|---|---|
| Uncontrolled Keywords: | Capacitated Vehicle Routing Problem, Cluster-First Route-Second, Metaheuristik, Gorilla Troop Optimization, Tabu Search, Iterated Local Search, Optimasi Logistik |
| Subjects: | T Technology > T Technology (General) > T57.6 Operations research--Mathematics. Goal programming |
| Divisions: | Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Information System > 59101-(S2) Master Thesis |
| Depositing User: | Akhdan Arifuddin |
| Date Deposited: | 25 Jul 2025 06:56 |
| Last Modified: | 25 Jul 2025 06:56 |
| URI: | http://repository.its.ac.id/id/eprint/121815 |
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