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Luhur Bayuaji
Universitas Budi Luhur
Computer Science & IT

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Perbandingan Genetic Algorithm, Nearest Neighbour, dan Particle Swarm Optimization untuk Penentuan Rute Pengiriman Barang Sandy Achmadi; Prabowo Murti Saputro; Luhur Bayuaji
Jurnal Algoritma Vol 23 No 1 (2026): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.23-1.3201

Abstract

The goods distribution process carried out by PT Saqo Putra Utama, a logistics transportation service company that delivers goods from warehouses to customers in the Jabodetabek area, is still performed manually. As a result, its effectiveness cannot be measured based on the travel distance from one location to another, leading to high operational costs for the company. This study aims to determine the shortest route for goods delivery by minimizing travel distance. The study compares and analyzes route determination results using three methods: Genetic Algorithm, Nearest Neighbour, and Particle Swarm Optimization. The comparison of these three algorithms in goods distribution routing aims to find a balance between processing speed and solution quality, namely the shortest distance or lowest cost. This research was conducted in the Jabodetabek area at PT Saqo Putra Utama, a logistics transportation service company that distributes goods from warehouses to customers. Based on the average calculation results of the three compared methods, it can be concluded that the best method for determining goods delivery routes at PT Saqo Putra Utama is the Genetic Algorithm method, with an average total distance of 222.57 km and an average total cost of IDR 355,809.66.
Co-Authors Prabowo Murti Saputro Sandy Achmadi