Optimizing Gas Station Control Officer Routes Using the Discrete Firefly Algorithm

This study investigates the application of the Firefly Algorithm (FA) to improve the routing efficiency of gas station control officers in Surabaya, Indonesia. It specifically targets the Asymmetric Clustered Traveling Salesman Problem (ACTSP), which involves clustering cities and determining the sequences of visits within each cluster. Drawing on observations of firefly behavior, the FA is utilized to address this intricate optimization problem. Through a case study, the research assesses the effectiveness of the FA in optimizing routes for gas station control officers, considering variations in travel costs among cities.