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All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Yusuf Afandi
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Optimasi Multiple Travelling Salesmen Problem Distribusi Produk PT Indomarco Adi Prima (Stock Point Nganjuk) dengan menggunakan Algoritma K-Means dan Algoritma Genetika (GKA) Yusuf Afandi; Imam Cholissodin; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 11 (2021): November 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Distribution is one thing that is very important so that a product can be delivered to customers / consumers. The job of a salesman is to visit the store or customer one day before the goods are shipped to offer the product and record the ordered goods. Factors that must be considered in the process are the time and costs required to be as minimal as possible. One aspect that can influence these two factors is the optimal travel route. In this study, the problem that we will try to solve is the optimization of product distribution routes at PT Indomarco Adi Prima (Stock Point Nganjuk) which has several points to be visited by more than one salesman one day before the distribution of goods. There are several processes to solve these problems, namely input data in the form of latitude and longitude data, then the data will be divided into several clusters according to the number of salesmen in the company, then each cluster will look for the shortest route for 5 working days and the end result is all the shortest routes from each cluster the total distance traveled will be calculated. Based on the results of tests that have been carried out using latitude and longitude data obtained from PT Indomarco Adi Prima (Stock Point Nganjuk), the most optimal route results with a total distance of 259.722337 km with a fitness of 0.385026. The most optimal parameter is when the population size is 1600, the number of generations is 800 with a combination of crossover rate (cr) 0.4 and mutation rate (mr) 0.6.
Co-Authors Bayu Rahayudi Imam Cholissodin