Using a heuristic approach to design personalized urban tourism itineraries with hotel selection

Abstract

Urban tourism is a worldwide form of tourism and is one of the most important social and economic impetus for urban development. The urban tourism market has been increasingly dominated by the demand for personalized experiences. Accordingly, this study aims to design personalized itineraries with hotel selection for multi-day urban tourists. A two-level heuristic approach is proposed, which embeds genetic algorithm, variable neighborhood search, and differential evolution algorithm into the structure of memetic algorithm. A case study in Xiamen, a coastal city in Southeast China, is carried out to evaluate the performance of our approach. Results of paired sample t-tests show that our proposed approach is remarkably superior to existing methods. In addition, compared with previous methods, our approach can design more reasonable and personalized itineraries for tourists.