Advanced Traveler Information Systems: Itinerary Optimisation Using Orienteering Problem Model and Genetic Algorithm

Traffic congestion is one of common urban problems. One of the main factors of congestion is the significant increase in the number motor vehicle growth that is not proportional with the growth of roads. To reduce traffic congestion, the government of Surabaya has made various efforts, one of which is the plan to encourage more people to use the public transportation system. To support the system a reliable transportation management system namely Surabaya Intelligent Transport Systems (SITS) is under development. As a part of SITS, this paper presents an advanced traveler information system which helps visitors planning their itinerary using public transport during their visit in the city. The problem is modeled as an orienteering problem (OP) and solved using genetic algorithm (GA). The model was developed upon six routes of `Angkot' which has been chosen. Travel time data is obtained through Google Maps. The contributions of this paper are two folds. First, we provide a public two datasets that is the dataset of travel time and score where each form of matrix. Upon the public datasets, future research, especially in the area of orienteering and optimisation problems could be encouraged. Second, initial algorithm based on the Genetic Algorithm to solve the problem. The computational experiments showed that the number of generations, the number of populations, the crossover probability, and the mutations probability play important role in the performance of the proposed algorithm. It is expected that this research can help the development of Surabaya Intelligent Transport System and the implementation of public transport revitalization in Surabaya.