Pengembangan Aplikasi Penentuan Rute Pengiriman Barang Berdasarkan Berat dan Time Windows Menggunakan Metode Nearest Neighbour dan Tabu Search

  • Putu Irvan Arya Purwadana Universitas Pendidikan Ganesha
  • I Made Candiasa Universitas Ganesha
  • I Nyoman Sukajaya Universitas Ganesha

Abstract

One of practical example of CVRPTW is delivery. Important factors in delivery are cost, speed, service and consistency. In order for these factors to be met optimally, the capacity and time windows must be considered. Capacity affects service and consistency, so the right route must be choosen with the shortest distance and the right capacity. Time windows affects on the speed and costs so that the delivery must be carried out according specified time and company operating hours. This research purpose to produce delivery routes that consider capacity and delivery time. There are two steps in calculation, which is clustering and searching of optimal delivery route. The clustering step uses a polar angle and the optimal route searching uses the nearest neighbour and the tabu search. The test show that the delivery route generated by the system can make efficiency distance of 12.18%, time of 5.54% and capacity of 1.27% and cost of 12.18%.

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References

[1] W. Irawan, M. Manaqib, and N. Fitriyati, “Implementation of the Model Capacited Vehicle Routing Problem with Time Windows with a Goal Programming Approach in Determining the Best Route for Goods Distribution,” J. Mat. Stat. dan Komputasi, vol. 17, no. 2, pp. 231–239, 2020, doi: 10.20956/jmsk.v17i2.11107.
[2] H. Prasetyo, A. L. Putri, and G. Fauza, “Biased Random Key Genetic Algorithm Design with Multiple Populations to Solve Capacitated Vehicle Routing Problem with Time Windows,” AIP Conf. Proc., vol. 1977, 2018, doi: 10.1063/1.5042908.
[3] R. Yohanes, S. Santoso, and R. M. Heryanto, “Penentuan Rute Distribusi yang Mempertimbangkan Multi Trips , Time Window , dan Simultaneous Pickup Delivery dengan Menggunakan Algoritma Sequential Insertion,” in Seminar Nasional Teknik Industri Universitas Gajah Mada, 2020, pp. 64–68.
[4] G. Melina Sari, R. Maini Heryanto, and S. Santoso, “Penentuan Rute Distribusi Menggunakan Model Integer Linear Programming dengan Metode Branch and Bound,” Go-Integratif J. Tek. Sist. dan Ind., vol. 1, no. 01, pp. 69–79, 2020, doi: 10.35261/gijtsi.v1i01.4265.
[5] Y. D. Putra, I. N. S. Kumara, N. Wayan, S. Aryani, I. Bagus, and A. Swamardika, “Metode Behaviorally Anchored Rating Scale ( BARS ),” Maj. Ilm. Teknol. Elektro, vol. 20, no. 1, pp. 104–111, 2021.
[6] I. W. A. S. Darma, “Implementation of Zoning and K-Nearest Neighbor in Character Recognition of Wrésastra Script,” Lontar Komput. J. Ilm. Teknol. Inf., vol. 10, no. 1, p. 9, 2019, doi: 10.24843/lkjiti.2019.v10.i01.p02.
[7] L. Leymena, C. S. B. W, and W. Sutopo, “Analisis Penentuan Rute Distribusi Menggunakan Metode Nearest Neighbor,” in Seminar dan Konferensi Nasional IDEC, 2019, p. E14.1-E14.7, [Online]. Available: https://idec.ft.uns.ac.id/wp-content/uploads/2019/05/ID119.pdf.
[8] N. Tiandini and W. Anggraeni, “Penerapan Metode Kombinasi Algoritma Genetika dan Tabu Search dalam Optimasi,” J. Tek. ITS, vol. 6, no. 1, 2017.
[9] W. Prasetyo and M. Tamyiz, “Vehicle Routing Problem dengan Aplikasi Metode Nearest Neihbor,” J. Res. Technol., vol. 3, no. 2, pp. 88–89, 2017.
[10] H. Hutomo and E. R. Sari, “Penyelesaian Capacitated Vehicle Routing Problem Menggunakan Algoritma Genetika Dan Nearest Neighbour Pada Pendistribusian Roti,” J. Mat., vol. 6, no. 2, pp. 52–62, 2017, [Online]. Available: http://journal.student.uny.ac.id/ojs/index.php/math/article/viewFile/6850/6591.
[11] C. Y. L and P. W. Endang, “Analisa Vehicle Routing Problem (VRP) Pada Produk Frozen Seafood dengan Menggunakan Algoritma Tabu Search (Studi Kasus : PT. Samudra Kencana Mina Sidoarjo),” vol. 12, no. 02, pp. 32–42, 2017.
[12] I. M. Ari Santosa, N. Nyoman Utami Januhari, I. P. Ramayasa, and I. Ketut Dedy Suryawan, “Comparison of Sweep and Tabu Search Methods in Searching for Item Delivery Routes based on Volume,” 2019 1st Int. Conf. Cybern. Intell. Syst. ICORIS 2019, vol. I, pp. 257–262, 2019, doi: 10.1109/ICORIS.2019.8874875.
[13] N. L. A. Ayuningrum and F. Y. Saptaningtyas, “Implementasi Algoritma Genetika dengan Variasi Crossover dalam Penyelesaian Capacitated Vehicle Routing Problem with Time Windows (CVRPTW) pada Pendistribusian Air Mineral,” J. Mat., vol. 6, no. 3, pp. 62–72, 2017.
[14] I. A. S. S. Anjani, L. Jasa, and I. R. Agung, “Rancang Bangun Sistem Minimarket Otomatis Berbasis IoT,” Maj. Ilm. Teknol. Elektro, vol. 19, no. 2, p. 255, 2020, doi: 10.24843/mite.2020.v19i02.p19.
[15] A. Purwadana, D. P. Githa, and D. P. Singgih, “Aplikasi Optimalisasi Pengiriman Barang Menggunakan Metode Tabu Search Berbasis Web,” vol. 6, no. 3, pp. 234–243, 2018.
[16] K. Meliantari, D. Putra Githa, and N. K. Ayu Wirdiani, “Optimasi Distribusi Produk Menggunakan Metode Cheapest Insertion Heuristic Berbasis Web,” J. Ilm. Merpati (Menara Penelit. Akad. Teknol. Informasi), vol. 6, no. 3, p. 204, 2018, doi: 10.24843/jim.2018.v06.i03.p07.
[17] Suryani, D. K. R. Kuncoro, and L. D. Fathimahhayati, “Perbandingan Penerapan Metode Nearest Neighbour dan Insertion untuk Penentuan Rute Distribusi Optimal Produk Roti pada UKM Hasan Bakery,” Profisiensi, vol. 6, no. 1, pp. 41–49, 2018.
[18] S. Martono and H. L. H. S. Warnars, “Penentuan Rute Pengiriman Barang Dengan Metode Nearest Neighbor,” Petir, vol. 13, no. 1, pp. 44–57, 2020, doi: 10.33322/petir.v13i1.869.
[19] P. M. Hasugian, “Pengembangan Aplikasi Untuk Mempermudah Pencarian,” J. Inform. Pelita Nusant., vol. 2, no. 1, pp. 1–5, 2017.
[20] N. L. A. M. Rahayu Dewi, R. S. Hartati, and Y. Divayana, “Penerapan Metode Prototype dalam Perancangan Sistem Informasi Penerimaan Karyawan Berbasis Website pada Berlian Agency,” Maj. Ilm. Teknol. Elektro, vol. 20, no. 1, p. 147, 2021, doi: 10.24843/mite.2021.v20i01.p17.
Published
2021-12-25
How to Cite
PURWADANA, Putu Irvan Arya; CANDIASA, I Made; SUKAJAYA, I Nyoman. Pengembangan Aplikasi Penentuan Rute Pengiriman Barang Berdasarkan Berat dan Time Windows Menggunakan Metode Nearest Neighbour dan Tabu Search. Majalah Ilmiah Teknologi Elektro, [S.l.], v. 20, n. 2, p. 299-306, dec. 2021. ISSN 2503-2372. Available at: <https://ojs.unud.ac.id/index.php/JTE/article/view/74393>. Date accessed: 27 june 2022. doi: https://doi.org/10.24843/MITE.2021.v20i02.P14.