IMPLEMENTASI HYPERGRAPH - PARTITIONING DAN ALGORITMA GENETIKA UNTUK PENENTUAN LINTASAN OPTIMAL DISTRIBUSI BARANG

Fitriani Halimatus Sadiyyah, - (2024) IMPLEMENTASI HYPERGRAPH - PARTITIONING DAN ALGORITMA GENETIKA UNTUK PENENTUAN LINTASAN OPTIMAL DISTRIBUSI BARANG. S1 thesis, Universitas Pendidikan Indonesia.

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Official URL: https://repository.upi.edu/

Abstract

Distribusi barang yang efisien merupakan kunci dalam manajemen logistik, yang memerlukan pemilihan jalur distribusi optimal untuk mencapai target pengiriman dengan total jarak minimal. Penelitian ini menggabungkan metode Hypergraph-Partitioning dan Algoritma Genetika untuk menentukan jalur distribusi barang yang optimal. Hypergraph-Partitioning digunakan untuk membagi barang yang akan didistribusikan secara seimbang ke beberapa kendaraan, sementara Algoritma Genetika diterapkan untuk menentukan lintasan distribusi terbaik di setiap partisi. Hasil penelitian menunjukkan bahwa metode Hypergraph-Partitioning berhasil membagi 62 pelanggan ke dalam dua partisi. Partisi pertama melayani 31 pelanggan yang harus dikunjungi dengan total permintaan sebanyak 865 buah roti, sedangkan partisi kedua juga melayani 31 pelanggan yang harus dikunjungi dengan total permintaan sebanyak 1.035 buah roti. Algoritma genetika kemudian digunakan untuk menemukan jalur terpendek untuk masing-masing partisi, sehingga menghasilkan solusi distribusi yang efisien. Penelitian ini membuktikan bahwa kombinasi metode Hypergraph-Partitioning dan Algoritma Genetika mampu menyelesaikan masalah pendistribusian barang yang optimal. Efficient distribution of goods is key in logistics management, which requires the selection of optimal distribution paths to achieve delivery targets with minimal total distance. This research combines Hypergraph-Partitioning and Genetic Algorithm methods to determine the optimal distribution path of goods. Hypergraph-partitioning is used to divide the goods to be distributed equally to several vehicles, while genetic algorithm is applied to determine the best distribution path in each partition. The results showed that the Hypergraph-Partitioning method successfully divided 62 customers into two partitions. The first partition serves 31 customers with a total demand of 865 loaves of bread, while the second partition also serves 31 customers with a total demand of 1,035 loaves of bread. A genetic algorithm was then used to find the shortest path for each partition, resulting in an efficient distribution solution. This research proves that the combination of Hypergraph-Partitioning method and genetic algorithm can solve the problem of optimal distribution of goods.

Item Type: Thesis (S1)
Additional Information: https://scholar.google.com/citations?hl=en&user=l5Y9bzgAAAAJ ID SINTA Dosen Pembimbing: Kartika Yulianti: 5979108 Ririn Sispiyati: 5986406
Uncontrolled Keywords: Algoritma Genetika, Hypergraph-Partitioning, Lintasan Terpendek, TSP Genetic Algorithm, Hypergraph-Partitioning, Shortest Path, TSP
Subjects: L Education > L Education (General)
Q Science > QA Mathematics
Divisions: Fakultas Pendidikan Matematika dan Ilmu Pengetahuan Alam > Jurusan Pendidikan Matematika > Program Studi Matematika (non kependidikan)
Depositing User: Fitriani Halimatus Sadiyyah
Date Deposited: 10 Sep 2024 07:42
Last Modified: 10 Sep 2024 07:42
URI: http://repository.upi.edu/id/eprint/123454

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