A stochastic approach to hotel revenue optimization

In this paper, we propose a network optimization model for hotel revenue management under an uncertain environment. The network optimization is in a stochastic programming formulation so as to capture the randomness of the unknown demand (unknown number of arrivals and length of stays). A novel approach of robust optimization techniques for stochastic programming is applied to solve the problem. We also discuss the strategies for hotel management to take into account of risk trade-off; different pricing policies; cancellations and no-show; early check-outs; extended stay and over-booking are discussed. We showed that our proposed model can be modified to adopt these strategic considerations.