Použití revenue managementu v hotelnictví

The main goal of this thesis was to create a model that would apply theoretical fundamentals of Revenue management. Firstly, the prediction model was created, which was forecasting the demand of hotel accommodation. For these purposes, linear regression and random forest algorithms were applied. To improve the accuracy of models, hyperparameters tuning was chosen. Results were compared using RMSE indicator. Subsequently, an optimization model was built in order to maximize hotel revenues. Mixed integer programming was the approach picked for building optimization model. As input parameters the results of the prediction model were used. Real data were provided by one unnamed smaller hotel. Data processing and modeling was done in R.