Genetic Algorithm To Optimize The Shortest Route for Indomaret Goods Suppliers

Abstract

This research examines the application of genetic algorithms to optimize the distribution of goods from suppliers to Indomaret outlets in the East Tegal District area by modeling the problem as the Traveling Salesman Problem (TSP). A genetic algorithm is applied to determine the most efficient distribution route, which aims to reduce travel distance and operational costs. Distance data between location points is taken from Google Maps, and the optimization process involves forming an initial population, selection based on fitness function, crossover, and mutation. The research results show that the genetic algorithm can produce an optimal solution with the shortest distance of 9,700 meters, and the highest fitness value of 0.0001031. These findings provide an overview of the effectiveness of genetic algorithms in handling TSP in the context of goods distribution and have the potential for further development in distribution and logistics applications