Recommendation of Scheduling Tourism Routes using Tabu Search Method (Case Study Bandung)
M Anranur Uwaisy, Z. K. A. Baizal, M Yusza Reditya · Procedia Computer Science · 2019
In 2019, the Indonesian Ministry of Tourism is in the process of improving the Go Digital program for the industrial era 4.0, where the internet has become one of the ways to determine travel destinations. However, currently, tourists still have difficulties obtaining detailed and complete information about tourist destinations, when visiting several destinations in one trip. Tourists are still having trouble estimating the distance and time needed for tourism independently, without having to depend on travel agents. These problems are often referred to as Traveling Salesman Problems (TSP). Therefore, we provide a solution to solve this TSP problem in the form of a system scheduling and searching route tourist using the tabu search method which enables tourists to find the optimal solution based on travel time, operational hours of tourist attraction, and the time limit of visits per day. Calculations in the tabu search method are combined with the concept of MAUT (Multi-Attribute Utility Theory) to determine the optimal tour based on several criteria: popularity, cost, and the number of attractions to be visited. Then, the test results of the tabu search method are compared with the firefly method. The result shows that the tabu search method is better than the firefly method, where there is an increase in accuracy of 48% in the calculation of fitness values, 47% in running time average, and 27% in the number of tours to be visited during 3 days of tour visits.