Jufri, Trizamsuar (2025) PERANCANGAN OPTIMASI RUTE PENGIRIMAN BUAH MENGGUNAKAN SAVING MATRIX DAN ALGORITMA GENETIKA UNTUK MENINGKATKAN EFISIENSI DISTRIBUSI. S2 thesis, Universitas Mercu Buana-Menteng.
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Abstract
Sektor pertanian Indonesia menghadapi tantangan signifikan dalam distribusi produk, terutama keterlambatan pengiriman (15-20%) dan kerusakan produk (10-15%) akibat ketidakoptimalan rute. Penelitian ini bertujuan membandingkan kinerja Saving Matrix (SM) dan Algoritma Genetika (AG) dalam mengoptimalkan rute pengiriman buah-buahan di Jawa Barat, dengan mempertimbangkan tiga faktor: jarak, biaya, dan waktu. Pendekatan mixed-method digunakan, menggabungkan analisis kualitatif (wawancara, observasi) dan kuantitatif (data sekunder perusahaan, simulasi Python). Data mencakup 13 titik distribusi, kapasitas truk 15 ton, dan variasi produk (jeruk, jambu biji, mangga, dll.) dengan masa simpan berbeda. Hasil menunjukkan SM efektif mengurangi jarak tempuh 23,2% (dari 920 km ke 706,8 km) dan biaya operasional 18,6% (Rp4,36 juta ke Rp3,55 juta) dalam waktu komputasi singkat (2-3 menit). Namun, AG unggul dalam kompleksitas tinggi, mencapai penghematan jarak 24,5% (694,2 km) dan biaya 19,7% (Rp3,50 juta) setelah 1,800 generasi. AG juga memprioritaskan produk rentan (stroberi, jambu biji) di awal rute, menurunkan kerusakan dari 15% ke 7% dan keterlambatan ke <10%. Keunggulan AG terletak pada kemampuan multi-objective optimization dengan penalty function untuk kapasitas dinamis dan adaptasi terhadap variasi permintaan. The Indonesian agricultural sector faces significant challenges in product distribution, particularly delays in delivery (15-20%) and product damage (10-15%) due to suboptimal routing. This study aims to compare the performance of the Saving Matrix (SM) and Genetic Algorithm (GA) in optimizing fruits delivery routes in West Java, considering three factors: distance, cost, and time. A mixed-method approach is employed, combining qualitative analysis (interviews, observations) and quantitative analysis (secondary data from companies, Python simulations). The data includes 13 distribution points, a 15-ton truk capacity, and a variety of products (oranges, guavas, mangoes, etc.) with different shelf lives. The results show that SM is effective in reducing the travel distance by 23.2% (from 920 km to 706.8 km) and operational costs by 18.6% (from IDR 4.36 million to IDR 3.55 million) within a short computation time (2-3 minutes). However, GA excels in high complexity, achieving a 24.5% reduction in distance (694.2 km) and a 19.7% reduction in cost (IDR 3.50 million) after 1,800 generations. GA also prioritizes perishable products (strawberry, guava) at the beginning of the route, reducing product damage from 15% to 7% and delays to less than 10%. The advantage of GA lies in its ability to perform multi-objective optimization with a penalty function for dynamic capacity and adaptability to variations in demand.
| Item Type: | Thesis (S2) |
|---|---|
| NIM/NIDN Creators: | 55322120010 |
| Uncontrolled Keywords: | Optimasi Rute, Saving Matrix, Algoritma Genetika, Efisiensi Distribusi, Logistik Route Optimization, Saving Matrix, Genetic Algorithm, Distribution Efficiency, Logistics |
| Subjects: | 600 Technology/Teknologi > 670 Manufacturing/Manufaktur, Pabrik-pabrik |
| Divisions: | Pascasarjana > Magister Teknik Industri |
| Depositing User: | OKTAFIYANI AZ ZAHRO |
| Date Deposited: | 07 Mar 2025 04:25 |
| Last Modified: | 07 Mar 2025 04:25 |
| URI: | http://repository.mercubuana.ac.id/id/eprint/94707 |
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