JSP_Dataset (Underlying Data).xlsx

Smart tourism destinations face challenges in efficiently scheduling services to meet the diverse needs of tourists while ensuring sustainability and resource optimization. This study explored the use of genetic algorithms (GAs) to optimize service scheduling and improve efficiency and customer satisfaction compared to traditional methods. Thematic analysis of collected data showed that GAs offer superior efficiency, increased customer satisfaction, and potential for enhanced tourist experiences and resource optimization. GAs could also adapt to changing circumstances and reoptimize schedules in real time. Further research and development in the use of GAs for service scheduling in tourism is recommended, including exploration of different types of tourism services and incorporation of real-time data for a competitive advantage and substantial value to the industry.