Genetic Algorithm and Local Search for Optimization of Tourism Trips as an Orienteering Problem

The development of the tourism sector experienced a decline from 2019 to 2021 due to the Covid-19 pandemic that affected the entire world. The lack of income managers receives causes many tourist destinations to be abandoned and bankrupt. This is also exacerbated by the location of tourist destinations that need better access. Through the Ministry of Tourism and Creative Economy, the Indonesian government seeks to improve the tourism sector by enhancing services and tourist visits. This research proposes an advanced travel information system with optimized travel plans to several tourist destinations based on travel time and destination popularity. The problem is modeled using the Orienteering Problem and solved using a genetic algorithm and local search (GALS). The results of the experiments demonstrate that the algorithm proposed in this study can efficiently and effectively solve the problem. In addition to suggesting an initial algorithm, another contribution of this research is the development of a new set of data for the orienteering problem. This dataset can motivate researchers to devise more advanced algorithms. The proposed system can generate travel plans with popular destinations and optimal travel times.