Algoritma Genetika untuk Penyelesaian Travelling Salesman Problem pada Rute Pendistribusian Barang Sicepat Ekspres

Abstract

The genetic algorithm is a form of random search that mimics the principles of natural biological evolution to find optimal solutions. The optimal solution search problem to be discussed is how to determine the shortest route for distributing goods. This research aims to study the application of the genetic algorithm in solving the Travelling Salesman Problem (TSP) for the distribution routes of goods at SiCepat Ekspres, specifically in the city of Medan. The Travelling Salesman Problem (TSP) is an optimization problem that seeks the shortest route to visit a number of locations exactly once and return to the starting point. The genetic algorithm is used because of its advantages in finding optimal solutions for complex and large-scale problems. This study limits the area to the city of Medan with 7 branch warehouses as destination points. From the calculations performed using the genetic algorithm with the help of Matlab software, the shortest route obtained is 72.6 km, where the journey starts from SiCepat Ekspress Medan (Sortation) - SiCepat Ekspress Medan Amplas - SiCepat Ekspress Medan Tuntungan - SiCepat Ekspress Medan Selayang - SiCepat Ekspress Medan Helvetia - SiCepat Ekspress Medan Labuhan - SiCepat Ekspress Medan Kota Matsum III - SiCepat Ekspress Medan Tembung and returns to SiCepat Ekspress Medan (Sortation). The research results show that the genetic algorithm can provide the shortest route solution, which can help improve the efficiency of goods distribution at SiCepat Ekspres.