Main Article Content

Ayu Manik Dirgayusari
I Made Dwi Putra Asana
I Gede Iwan Sudipa
Rini Komalasari
Sugihya Artha Dwipayani

Abstract

Consumer needs for speed of delivery of goods and retrieval of goods are very important in the world of cargo. One of them is TAM CARGO BALI where couriers have difficulty in delivering goods during the process of determining the shipping route route. This makes the need for an information system to determine accuracy in the selection of the initial and subsequent paths to facilitate couriers, with the Traveling Salesman Problem (TSP) genetic algorithm with optimization problems, namely visiting every place from a set of specified places once and only once. then return to the starting place at the end of the travel route with the distance, the minimum time and cost and the results of distance optimization by generating chromosomes from the specified route make a sequence of the shortest path from the starting point of TAM CARGO BALI back to the end point at TAM CARGO BALI. Traveling Salesman Problem TSP is the search for the shortest route or minimum distance by a salesman from a city to n-city exactly once and back to the initial city of departure where the weight on the side is the distance. This TSP route contains all the vertices on the graph exactly one turn. After the generation of chromosomes, the generation selection process, crossover and mutation are carried out to get the best fitness value for each generation. The generation process will be repeated until the maximum generation is the 10th generation. The application that has been successfully built can determine the best route visualized on the map. Application testing is carried out by testing the system's functional and manual calculations according to the route output generated by the system.

Downloads

Download data is not yet available.

Article Details

How to Cite
Dirgayusari, A. M., Asana, I. M. D. P., Sudipa, I. G. I., Komalasari, R. and Dwipayani, S. A. (2021) “Application for Determining Shipping Routes at Cargo Companies with Genetic Algorithms”, Jurnal Mantik, 5(2), pp. 1034-1044. doi: 10.35335/jurnalmantik.Vol5.2021.1456.pp1030-1040.
References
[1] R. Jadczak, “Traveling salesman problem: approach to optimality,” Przedsiebiorczosc i Zarz., vol. 15, no. 2, pp. 157–169, Aug. 2014.
[2] W. T. Ina, S. O. Manu, and T. Y. Matahhine, “PENERAPAN ALGORITMA GENETIKA PADA TRAVELLING SALESMAN PROBLEM (TSP) (STUDI KASUS: PEDAGANG PERABOT KELILING DI KOTA KUPANG),” J. Media Elektro, pp. 53–58, Apr. 2019.
[3] J. Scholz, “Genetic Algorithms and the Traveling Salesman Problem a historical Review,” pp. 1–8, 2019.
[4] P. Kora and P. Yadlapalli, “Crossover Operators in Genetic Algorithms: A Review,” Int. J. Comput. Appl., vol. 162, no. 10, pp. 34–36, 2017.
[5] M. W. Tsai, T. P. Hong, and W. T. Lin, “A two-dimensional genetic algorithm and its application to aircraft scheduling problem,” Math. Probl. Eng., vol. 2015, 2015.
[6] T. S. Jaya, “Pengujian Aplikasi Dengan Metode Blackbox Testing Boundary Value Analysis (Studi Kasus: Kantor Digital Politeknik Negeri Lampung),” J. Inform. J. Pengemb. IT, vol. 3, no. 2, pp. 45–46, 2018.