Pencarian Rute Terpendek menggunakan Algoritma Genetika (Studi Kasus : Pengoptimalan Mobilitas Kota Salatiga Terhadap Kota-Kota Tetangga)
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The increase in population in an area has a significant impact on vehicle density in that area. The problem that often arises is traffic jams that occur on several routes at once. This factor is a common problem, which is quite disturbing to the public and road users. To overcome this problem, the genetic algorithm method is used as a solution method. This case study was set at the regional or city level around Salatiga City, including Ambarawa City, Semarang City, Boyolali City, Solo City and Magelang City. By using the genetic algorithm method, the fastest route with the shortest distance can be found. The Genetic Algorithm used in this research allows optimal shortest route search results. Apart from that, this research can also minimize the distance and travel time of several alternative routes obtained, thus providing significant benefits in developing the transportation system in the region.
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Melladia, M. (2020). Algoritma Genetika Menentukan Jalur Jalan dengan Lintasan Terpendek (Shortest Path). Prosiding SISFOTEK, 4(1), 112-117.
Mubarok, A. Y., & Chotijah, U. (2021). Penerapan Algoritma Genetika Untuk Mencari Optimasi Kombinasi Jalur Terpendek Dalam Kasus Travelling Salesman Problem. Jurnal Teknologi Terpadu, 7(2), 77-82. DOI: https://doi.org/10.54914/jtt.v7i2.424.
Muhandhis, I., Shubhan, M., Dani, H. I., Rakasyah, A., Ritonga, A. S., & Sari, M. U. (2023). Pencarian Rute Terpendek Tim Promosi Kampus dengan Menggunakan Algoritma Genetik. Jurnal Teknologi dan Manajemen, 4(1), 6-12. DOI: https://doi.org/10.31284/j.jtm.2023.v4i1.4106.
Oktaviandi, R. B., Hadi, M. S. T., Santoso, A. G., & El Maidah, N. (2019). Perbandingan Algoritma Genetika dengan Algoritma Greedy Untuk Pencarian Rute Terpendek. INFORMAL: Informatics Journal, 3(1), 6-11.
Ramadhania, S. E., & Rani, S. (2021). Implementasi kombinasi algoritma genetika dan tabu search untuk penyelesaian travelling salesman problem. AUTOMATA, 2(1).
Saputra, I., & Ahmad, D. (2020). Algoritma Genetika Untuk Menentukan Jalur Terpendek Wisata Kota Bukittinggi. Journal of Mathematics UNP, 5(1). DOI: http://dx.doi.org/10.24036/unpjomath.v5i1.8905.
Tohari, A., & Astuti, Y. P. (2023). PENERAPAN ALGORITMA GENETIKA DALAM MENENTUKAN RUTE TERPENDEK PT. POS CABANG LAMONGAN. MATHunesa: Jurnal Ilmiah Matematika, 11(03), 458-467.
Zukhri, Z. (2014). Algoritma Genetika Metode Komputasi Evolusioner untuk Menyelesaikan Masalah Optimasi. Yogyakarta: Andi Offset.