IMPLEMENTASI LINEAR PROGRAMMING PADA MODEL CVRPP UNTUK PENGELOLAAN OPERASIONAL LOGISTIK
DOI:
https://doi.org/10.31000/jika.v8i4.12068Abstrak
Perusahaan logistik merupakan perusahaan yang memiliki kekhususan dalam penyediaan layanan logistik, yang membantu dalam mengelola fungsi rantai pasokan termasuk pergudangan, distribusi, dan transportasi. Salah satu perusahaan logistik di kota Bandung,yang bergerak di bidang layanan jasa logistik dan memiliki layanan pickup yang bertugas untuk memasarkan produk serta melakukan layanan penjemputan barang. Pada layanan ini, tahap perencanaan aktivitas seperti rute dan kapasitas kendaraan merupakan tahapan yang penting. Namun, pada penerapannya perusahaan ini belum menerapkan aktifitas perjalanan dengan rute terbaik atau hanya berdasar pengalaman driver, serta kurang memaksimalkan kapasitas angkut kendaraan. Capacitated Vehicle Routing Problem with Pickup (CVRPP) adalah metode yang digunakan dalam penanganan masalah ini. Penelitian ini bertujuan pada pembuatan model pencarian jarak dan pemaksimalan kapasitas kendaraan yang dapat meningkatkan efisiensi operasional dalam pengelolaan kapasitas dan rute logistik. Untuk mencapai tujuan penelitian, Linear Programming dengan bahasa pemrograman Python digunakan sebagai proses perhitungan yang digunakan dan menghasilkan solusi terbaik. Hasil penelitian menunjukkan bahwa rute yang terbentuk menggunakan Linear Programming menghasilkan jarak paling pendek diantara rute lainnya dengan penghematan jarak sebesar 19.99% pada analisis dan 31.92% pada aplikasi. Hal itu juga didukung dengan evaluasi dengan Optimality Gap yang bernilai 0% atau solusi yang ditemukan adalah optimal atau sangat baik.Referensi
Al Amin, I. H., & Wahyudiyono, W. (2021). Implementasi Metode Haversine Untuk Pencarian Optical Distribution Point. Jutnal Ilmiah Teknologi Informasi, 13(1).
Bantacut, T., & Fadhil, R. (2018). Penerapan LOGISTIK 4.0 dalam Manajemen Rantai Pasok Beras Perum BULOG: Sebuah Gagasan Awal. Jurnal Pangan, 27(2). https://doi.org/https://doi.org/10.33964/jp.v27i2.371
Basriati, S., & Aziza, D. (2017). Penentuan Rute Distribusi pada Multiple Depot Vehicle Routing Problem (MDVRP) Menggunakan Metode Insertion Heuristic (Studi Kasus : Orange Laundry di Kota Pekanbaru). Jurnal Sains Matematika dan Statistika, 3. https://doi.org/10.24014/jsms.v3i1.4465
Bernardino, R., & Paias, A. (2024). The family capacitated vehicle routing problem. European Journal of Operational Research, 314. https://doi.org/10.1016/j.ejor.2023.10.042
Chi, J., & He, S. (2023). Pickup capacitated vehicle routing problem with three-dimensional loading constraints: Model and algorithms. Transportation Research Part E: Logistics and Transportation Review, 176. https://doi.org/10.1016/j.tre.2023.103208
Claudiu Pop, P., Zelina, I., LupÅŸe, V., Pop Sitar, C., & Chira, C. (2011). Heuristic Algorithms for Solving the Generalized Vehicle Routing Problem. International Journal of Computers Communications & Control, 6(1). https://univagora.ro/jour/index.php/ijccc/article/view/2210
Efendi, Y. (2022). Perancangan Vehicle Routing Problem Menggunakan Algoritma Nearest Neighbor Dan Local Search Guna Optimasi Biaya Distribusi Pada Pt Madubaru. dspace.uii.ac.id/handle/123456789/40110
Eviana, A., Fauzan, Abd. C., Harliana, & Putra, F. N. (2022). Komparasi Jarak Euclidean dan Jarak Manhattan untuk Deteksi Covid-19 Melalui Citra CT-Scan Paru-Paru. Jurnal Sistem Komputer, 11(2). https://doi.org/https://doi.org/10.34010/komputika.v11i2.5380
Fikri, A. J., Aini, S., Sukandar, R. S., Sfiyanah, I., & Listiasari, D. (2021). Optimalisasi Keuntungan Produksi Makanan Menggunakan Pemrograman Linear Melalui Metode Simpleks. Jurnal Bayesian, 1.
Jiang, H., Lu, M., Tian, Y., Qiu, J., & Zhang, X. (2022). An evolutionary algorithm for solving Capacitated Vehicle Routing Problems by using local information. Applied Soft Computing, 17. https://doi.org/https://doi.org/10.1016/j.asoc.2022.108431
Koc, C., Laporte, G., & Tukenmez, I. (2020). A review of vehicle routing with simultaneous pickup and delivery. Computers & Operations Research, 122. https://doi.org/https://doi.org/10.1016/j.cor.2020.104987
Kristina, S., Sianturi, R. D., & Husnadi, R. (2020). Penerapan Model CVRP Menggunakan Google Or-Tools Untuk Penentuan Rute Pengantaran Obat Pada Perusahaan Pedagang Besar Farmasi. Jurnal Telematika, 15.
Limei, H., Tannady, H., & Nurprihatin, F. (2018). Meminimumkan Biaya Transportasi pada Capacitated Vehicle Routing Problem dengan Metode Heuristik. Seminar Rekayasa Teknologi Semrestek 2018. https://teknik.univpancasila.ac.id/semrestek/prosiding/index.php/12345/article/view/277
Liu, X., Chen, Y.-L., Por, Y. L., & Ku, C. S. (2023). A Systematic Literature Review of Vehicle Routing Problems with Time Windows. Sustainability, 15(15).
Mazzuco D., Oliveira D., & Frazzon E.M. (2017). State of the art in simulation-based optimization approaches for vehicle routing problems along manufacturing supply chains. 24th International Conference on Production Research. https://doi.org/State of the art in simulation-based optimization approaches for vehicle routing problems along manufacturing supply chains
Moghdani, R., Salimifard, K., Demir, E., & Benyettou, A. B. (2021). The green vehicle routing problem: A systematic literature review. Journal of Cleaner Production, 279. https://doi.org/https://doi.org/10.1016/j.jclepro.2020.123691
Moudya, F., Rarasati, N., & Syafmen, W. (2023). Optimisasi Rute Pada Cvrp Dalam Pendistribusian Gas Oksigen Menggunakan Algoritma Clarke And Wright Savings. Jurnal Pendidikan Matematika dan Matematika, 9. https://doi.org/10.24853/fbc.9.1.105-118
Ngo, Q.-H. (2023). The effectiveness of market orientation in the logistic industry: A focus on SMEs in an emerging country. Heliyon, 9(7). https://doi.org/https://doi.org/10.1016/j.heliyon.2023.e17666
Novindri, G. F., & Saian, P. O. N. (2022). Implementasi Flask Pada Sistem Penentuan Minimal Order Untuk Tiap Item Barang Di Distribution Center Pada PT XYZ Berbasis Website. Jurnal MNEMONIC, 5. https://doi.org/10.36040/mnemonic.v5i2.4670
Nurmayanti, L., & Sudrajat, A. (2021). Implementasi linear programming metode simpleks pada home industry khasanah sari karawang. Jurnal Manajemen, 13(3). https://doi.org/https://doi.org/10.30872/jmmn.v13i3.10085
Patel, M., & Patel, N. (2019). Exploring Research Methodology: Review Article. International Journal of Research and Review, 6(3). https://www.ijrrjournal.com/IJRR_Vol.6_Issue.3_March2019/IJRR0011.pdf
Ridwan, Saputra, M. A., & Indriyanti, R. (2020). Penerapan Logistik 4.0 Dalam Pendistribusian Barang Produksi Pt. Solusi Bangun Indonesia Tbk. Cilacap. Prosiding Seminar Sosial, 2(1). https://e-journal.akpelni.ac.id/index.php/prosiding-nsmis/article/view/154
Sitompul, C., & Manasye Horas, O. (2021). A Vehicle Routing Problem with Time Windows Subject to the Constraint of Vehicles and Good’s Dimensions. International Journal of Technology (IJTech), 12(4).
Suroso, J. S. D., & Nugroho, P. (2023). Analisis Optimalisasi Produksi dengan Linear Programming Melalui Metode Simpleks (Studi Kasus UMKM Aqisa Rumah Rosella Surabaya). Jurnal Kajian Ilmu Manajemen, 3. https://doi.org/10.21107/jkim.v3i2.18918
Wijayanto, C., & Susetyo, Y. A. (2022). Implementasi Flask Framework Pada Pembangunan Aplikasi Sistem Informasi Helpdesk (SIH). Jurnal Ilmiah Penelitian dan Pembelajaran Informatika, 7.
Unduhan
Diterbitkan
Terbitan
Bagian
Lisensi
License and Copyright Agreement
In submitting the manuscript to the journal, the authors certify that:
- They are authorized by their co-authors to enter into these arrangements.
- That it is not under consideration for publication elsewhere,
- That its publication has been approved by all the author(s) and by the responsible authorities – tacitly or explicitly – of the institutes where the work has been carried out.
- They secure the right to reproduce any material that has already been published or copyrighted elsewhere.
- They agree to the following license and copyright agreement.
Copyright
Authors who publish with International Journal of Advances in Intelligent Informatics agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License (CC BY-SA 4.0) that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.Â
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
Licensing for Data Publication
International Journal of Advances in Intelligent Informatics use a variety of waivers and licenses, that are specifically designed for and appropriate for the treatment of data:
Open Data Commons Attribution License, http://www.opendatacommons.org/licenses/by/1.0/ (default)
Creative Commons CC-Zero Waiver, http://creativecommons.org/publicdomain/zero/1.0/
Open Data Commons Public Domain Dedication and Licence, http://www.opendatacommons.org/licenses/pddl/1-0/
Other data publishing licenses may be allowed as exceptions (subject to approval by the editor on a case-by-case basis) and should be justified with a written statement from the author, which will be published with the article.
Open Data and Software Publishing and Sharing
The journal strives to maximize the replicability of the research published in it. Authors are thus required to share all data, code or protocols underlying the research reported in their articles. Exceptions are permitted but have to be justified in a written public statement accompanying the article.
Datasets and software should be deposited and permanently archived inappropriate, trusted, general, or domain-specific repositories (please consult http://service.re3data.org and/or software repositories such as GitHub, GitLab, Bioinformatics.org, or equivalent). The associated persistent identifiers (e.g. DOI, or others) of the dataset(s) must be included in the data or software resources section of the article. Reference(s) to datasets and software should also be included in the reference list of the article with DOIs (where available). Where no domain-specific data repository exists, authors should deposit their datasets in a general repository such as ZENODO, Dryad, Dataverse, or others.
Small data may also be published as data files or packages supplementary to a research article, however, the authors should prefer in all cases a deposition in data repositories.