Modelling and an application of a dynamic room pricing problem for hotel industry

Nowadays, one of the most important goals of all companies is to increase the total income as much as possible. Companies aim to maintain their strong stance against their competitors and ensure the continuity of their activities by creating a competitive environment where they can generate the highest income with the lowest costs and maintain their current service/product quality. In this direction, companies use many methods in order to make accurate demand forecasts and correct pricing of the services/products to be sold. In this thesis, in terms of hotels operating in the hotel sector, dynamic pricing, taking into account variables such as demand amount, cancellation amount, length of stay, number of days left to stay and room type, providing the highest possible income and accordingly the highest occupancy rates, aimed to achieve. In the study, real-life data from a hotel operating in the hotel industry were used. First of all, demand forecasting application was made by using the data received from the hotel and "Artificial Neural Networks", one of the heuristic methods. The estimated data obtained by using the demand forecasting application was transferred to the dynamic mathematical pricing model, which was created by taking into account the sectoral rules and the constraints encountered in real applications. And finally the solution is obtained. The results obtained by solving the model and the results obtained in real life applications were compared with each other. As a result of the applications, it was concluded that it is possible to use the mathematical dynamic pricing model in the hotel industry. In addition, the mathematical model which is created is flexible enough to be adapted to different sectors by making some changes.