| dc.description.abstract | Traveling Salesman Problem (TSP) is a classic combinatorial optimization problem, one of the optimization problems that can be applied to various activities such as finding the shortest path. The optimization problem in TSP is the most widely discussed and has become the standard for testing computational algorithms. TSP is a good object to test optimization performance. With scientific developments in the field of informatics, many researchers have optimized the application of algorithms to solve the Traveling Salesman Problem (TSP). In this study, researchers used a combination of Ant Colony Tabu Search – Firefly Algorithm Tabu Search (ACTS-FATS). The combination is doneto overcome Premature Convergence (trapped local optimum) which is a shortcoming of the ant colony algorithm, get the best running time by looking at the process of each point movement with the ant colony and firefly methods. After testing, the Eil51 dataset obtained an increase in accuracy of 17%, while the Eil76 dataset was 3.45%, Oliver30 1.40%, KroA100 4.88%, KroA200 3.1% and the TSPLIB95 A280 dataset was 3.47% with a running time of 27.79%. | en_US |
