IMPLEMENTASI ALGORTIMA GENETIKA UNTUK OPTIMALISASI RUTE PENGIRIMAN PESANAN DI RESTO PAK LANJAR SLEMAN

Abstract

Multi-destination travel is one of the problems in the Traveling Salesman Problem (TSP), which has a large problem space if solved combinatorially. This study aims to design and implement a Genetic Algorithm model to provide route recommendations for order deliveries at Resto Pak Lanjar, Sleman. The proposed Genetic Algorithm takes into account both symmetric and asymmetric distances. The route recommendations consider not only the distance but also the travel time, which is obtained using Google Maps API. The encoding scheme uses permutation encoding, parent selection is done through roulette-wheel selection, with order crossover as the crossover method and swap mutation as the mutation method. The algorithm also ensures that the best individual from a given generation is not lost during the evolutionary process. This study fills the gap in the literature, especially in applying Genetic Algorithms for route optimization in small restaurants by considering both time and distance factors. The experimental results show that for fewer than 8 objects, the optimal population size consists of 30 individuals, while for more than 8 objects, the optimal population size consists of 180 individuals. The stopping criterion is set when the highest fitness value remains unchanged for 30 consecutive generations. The optimal combination of crossover and mutation probabilities is {0.5:0.5}.