Creation of historical and cultural travel route planning using metaheuristic algorithms: An example of Şanlıurfa province

In today's rapidly advancing technological landscape, the interaction of users with technology is escalating across all age groups. With the swift progression of technology, users are diversifying into various sectors. Modern mobile devices and tablets host many applications that people use in their daily lives. Through navigation applications, they can reach unfamiliar addresses, find the nearest bus or taxi stops, send documents such as sound, video, and photos via email, engage in visual or text-based communication with numerous individuals on social media, and conduct various transactions, including shopping. However, in many cities, including Şanlıurfa province of Türkiye, a digital application is deficient in providing comprehensive guidance on historical sites. Local and foreign tourists visiting Şanlıurfa, even if they wish to explore historical sites, face difficulties acquiring sufficient information about these places and planning their visit. Time constraints during trips, uncertainties about the order in which cultural sites to visit, and transportation difficulties adversely impact tourists' experiences. At this juncture, there is a significant need to develop a mobile application that guides users planning to visit historical sites in Şanlıurfa. This application should provide visual, textual, and auditory information, enable users to share their experiences and create an optimal route with minimal cost. This application aims to solve the traveling salesman problem, providing users with the shortest and most effective route. The proposed application seeks to minimize the challenges tourists face when exploring historical sites in Şanlıurfa, making it easier to navigate purposefully. Developed to assist in discovering the historical riches of Şanlıurfa, this digital application has the potential to enhance the tourism experience significantly. This thesis comprises two stages. The first stage involves design using the C# programming language on the Microsoft Visual Studio tool. In this phase, the Ant Colony Algorithm and Genetic Algorithm are compared in terms of time, distance, and the iteration direction where the best route is found, and the experimental results are examined. In conclusion, it was observed that the Ant Colony Algorithm outperforms the Genetic Algorithm in terms of time and route distance. In the second stage, the Ant Colony Algorithm, an artificial intelligence algorithm, was recoded using Dart-Flutter, a contemporary mobile application development language. Visual screens were configured, and the minimum route planning for historical sites on Google Maps was transformed into an AI-supported intelligent tourism guide. The application is intended for use on all IOS and Android mobile devices, providing users with an AI-assisted smart tourism guide. This study holds significance for those wishing to implement artificial intelligence in the tourism sector and serves as a guiding light for tourists visiting the Şanlıurfa province.