Advanced Traveller Information Systems: Itinerary Optimisation Using Orienteering Problem Model and Great Deluge Iterative Local Search (Case Study: Angkot's Route in Surabaya)

Congestion is one of the biggest problems for big cities in the world, this is caused by many things ranging from urbanization, population increase and the problem of the number of private vehicles that are more widely used than public transport provided. The method used to model the problem is Orienteering Problem with distance and time taken using Google Maps and determination based on the number of city transportation on the route, with the route code used is M, S, TWM, U, UBB, WB. Several assumptions were also added to model problems to model realistic conditions. Dijkstra's algorithm is also used to find the shortest path between points that can help get optimal solution results. The search for a solution of the model has been made using Great Deluge Iterative Local Search to find the best solution from the model and use the repeated insert, swap and delete method to get the best possible solution. Iterative local search provides the speed and efficiency in searching for solutions. In this research, it is found that the orienteering problem can model six Angkot's routes into network models that are connected to each other and become a great route that can be search from one point to all points. The Great Deluge Iterative Local Search algorithm can also improve results from searching for a feasible initial solution using a random manner with an 81-minute travel time and a 4010 score.