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All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Muhammad Aghni Nur Lazuardy
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Optimasi Rute Multiple Travelling Salesman Problem Pada Distribusi Es Batu Dengan Algoritme Artificial Bee Colony (ABC) Muhammad Aghni Nur Lazuardy; Imam Cholissodin; Muhammad Tanzil Furqon
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 12 (2018): Desember 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The distribution is done to improving the productivity of the company. A strategy in the process of distribution is required primarily in determining the distribution route. An optimal route is essential in product distribution especially ice cubes. A company needs to send its products to multiple addresses, because the numbers of shipping addresses and varying distances creates a problem such as needing a long time to reach the destination. In solving these problem need a system that has a purpose to help the distribution process with the number of sales more than one, the problem is named Multiple Travelling Salesman Problem (M-TSP). One of the methods that can solve the problem of M-TSP is Artificial Bee Colony (ABC) algorithm which compared to other algorithm based on swarm intelligence. The initial process of ABC algorithm looks for random ice cubes distribution routes based on customer's ordering data. Furthermore swapping and insertion route is done then taken the route with optimal fitness. The last is comparison with the initial route whether the result is better or not. The test result show the numbers of optimal parameters are 23 size problems, 80 pop sizes, 10 limits, and 600 iterations. From these parameters obtained average fitness value based on system optimization of 0,078163 and manual selection of routes the sales goes through obtain average fitness value of 0,043472, with the result that path selection can be optimized by system.
Co-Authors Imam Cholissodin Muhammad Tanzil Furqon