دانلود رایگان مقاله انگلیسی روش های تجزیه برای تخصیص اتاق پویا در مدیریت درآمد هتل - الزویر 2018

Abstract

Long-term stays are quite common in the hotel business. Consequently, it is crucial for the hotel managements to consider the allocation of available rooms to a stream of customers requesting to stay multiple days. This requirement leads to the solving of dynamic network revenue management problems that are computationally challenging. A remedy is to apply decomposition approaches so that an approximate solution can be obtained by solving many simpler problems. In this study, we investigate several room allocation policies in hotel revenue management. We work on various decomposition methods to find reservation policies for advance bookings and stay-over customers. We also devise solution algorithms to solve the resulting problems efficiently

7. Conclusion

In this study, we work on the dynamic room allocation problem in hotel revenue management. Due to the complexity of this problem, we concentrate on several approximation methods. We analyze the structural properties of the problem and present day- and pair-based decomposition approaches that can handle the walk-in and the stay-over customers. First, we work on the day-based decomposition methods. Day-based decomposition generates independent subproblems for each day and, hence, it cannot store the number of reserved rooms for each product. Therefore, incorporating the stay-over customers becomes a challenge. In the second part, we work on the stay-over extension. To the best of our knowledge, the dynamic programming model that includes the stay-over customers has not been proposed in the literature before. We first focus on the single-day stay-over problem. By extending the work of Birbil et al. (2014), we propose a solution method. Second, we consider the multi-day stay-over problem and present a two-period approximation, which combines the pair-based decomposition with the deterministic linear programming. We conduct a thorough computational study and investigate the performances of our proposed models along with some well-known approaches used in the literature. Our computational experiments indicate that the proposed policies perform well. The performance gaps are especially significant when the hotel’s daily capacity is tight and the stay-over probability is high.

As we mentioned in Section 5.2, our stay-over models can be extended to several other applications in hotel RM. Recently, hotel reservation systems have started to offer late checkout option to their customers. Late checkout requests can be considered as a special case of stay-over problem where the customers can extend their stay until the allowed time specified by the hotel. Following the same construction as for the stay-over model, we can obtain the reservation policies for late checkouts. Another important issue in hotel revenue management is overbooking. Similarly, the overbooking option can be incorporated in the multi-day stay-over model and it can also be solved in two stages. However, it is important to note that preallocating the hotel capacity to even more pairs and determining the individual overbooking limit for each pair may poorly affect the control of hotel capacity network-wide. Incorporation of the overbooking option is a potential topic for future research.