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

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Optimasi Rute Distribusi Lokal Buah Segar Menggunakan Algoritme Genetika (Studi Kasus: PT Great Giant Pineapple) Asfie Nurjanah; Agus Wahyu Widodo; Muhammad Tanzil Furqon
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 4 No 12 (2020): Desember 2020
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

In terms of time and financial costs, transportation and distribution are the biggest challenges for the fresh produce industry in Indonesia. On time delivery and the freshness of the product when it reaches the customer are demands that must be met by the company, as experienced by PT Great Giant Pineapple. To solve this problem, a system is needed to improve the quality of distributing products by minimizing distribution distances by finding the optimal route for the vehicle by considering travel time, service time and vehicle transport capacity. This problem in determining the optimal distribution route is known as the Vehicle Routing Problem with Time Windows (VRPTW). Genetic algorithm is one method that can be used to solve the VRPTW problem. The genetic algorithm uses a permutation representation where the chromosome length represents the number of subscribers. The search for solutions is carried out by combining chromosomes and then processed using genetic operators (mutation, crossover, and selection) by initializing genetic operators (population size, number of generations, crossover probability, and mutation probability). The test results show that the distribution route optimization using a genetic algorithm can reduce the travel time in distributing goods by 1 hour 37 minutes with the highest fitness value obtained at population size 120, the number of generations 100, the combination of crossover probability value 0.4 and mutation probability 0.6.
Co-Authors Agus Wahyu Widodo Muhammad Tanzil Furqon