RoomTetris: an optimal procedure for committing rooms to reservations in hotels

研究目的 – 很多酒店, 特别是私人、家庭经营型、或者精品酒店, 在客人预定后立刻分派指定的房间 给客人。这往往是因为独立房间售卖(没有特殊房型概念)或者因为客人在预定时, 工作人员手动指 派房间, 亦或者是因为预订系统与渠道管理系统链接, 直接在预定后指派房间号。这种早期的分派程 序是不优化的, 往往在酒店住房率高的时候, 会造成一些不必要的房间预定失败, 继而带来的利润损 失。本论文旨在研究不同房间指派参数配置, 包括最优系统(RoomTetris), 使得酒店达到更高住房 率的同时产生高利润。 研究设计/方法/途径 – 本论文采用理论讨论和实验等研究方法, 并展示了提出的RoomTetris参数的最 优性。本论文还将其参数放在不同的情景中做实验, 以显示其提高酒店针对随机或者次优化分派的最 佳启发式策略中的住房率。 研究结果 – 研究结果表明智能型分派参数能够大大降低预定失败率(预定需求不能符合酒店房型供 给), 并且提高住房率和利润。住房时间并不是必须的参数, 极具个性化服务, 比如让客人选房间号, 可能导致利润损失(因为最优房间分派无法实现), 房型的设计也应该参与到最优房间分派的效果中 来。 研究理论限制/启示 – 预定取消和超额预定的情况也应该加入到分析中来。第二种对于拥有不止一 种房型的酒店来说, 可能增加房间分派的情况在于为客人升级房型, 这样可以将客人转到其他适合房 型以解决房间分派问题。此外, 更复杂系统兼容财务管理系统应该被考量, 有的时候, 房间的成本取决 于客人的数量。 研究实践启示 – 由于最优算法的住房率区别在于旺季和高预定时段, 也就是高房间价格和高预定量, 本论文提出的最佳算法将提高主要财务指标, 比如RevPAR(平均客房收益)。由于房间分配系统可 以完全实现自动化, 那么采用智能分派系统无疑是有效酒店管理中的优质选择。 研究原创性/价值 – 据作者所知, 此文章是首篇关于此类话题的研究优质算法(且被证实其最佳)。 关键词: 酒店管理 、优质化 、酒店模拟程序 、参数 文章类型: 研究型论文

Purpose Many hotels allocate guests to specific rooms immediately after reservation. This happens because individual rooms are sold (and there is no concept of room type) or because the assignment is done by hand at reservation or because of a connection with a channel manager, which is immediately fixing the room number after a reservation request. This early allocation is suboptimal, and it causes the unnecessary rejection of some reservations when the hotel has a high occupancy level. The purpose of this paper is to investigate different room allocation algorithms, including an optimal one (called RoomTetris), aiming at higher occupancy levels and profitability. Design/methodology/approach The methodology is based on theoretical results and experimentation. The optimality or the proposed RoomTetris algorithm is demonstrated. Experiments are executed in different contexts, including realistic ones, through the adoption of a hotel simulator, to measure the improvements in the occupancy rate of the optimal and heuristic strategies with respect to random or sub-optimal assignments of rooms. Findings The main results are that smart allocation algorithms can greatly reduce the rejection rate (reservation requests which cannot be fit into the hotel room plan) and improve the occupancy level, the percentage of available rooms or beds sold for the various periods. Research limitations/implications This analysis can be extended by considering cancellations and overbookings. A second possibility to add flexibility in room allocation for hotels having more than one type of rooms is that the hotel can upgrade and offer a high-price room to the customer, which given an even large flexibility to fix rooms by shifting customers to other compatible types. In addition, more complex integrations with revenue management can also be considered, for cases in which the cost of a room depends on the number of guests. Practical implications Given that the difference in occupancy rate of the optimal algorithm is particularly large in high season and high-request periods, periods which are usually associated to higher rates and higher volumes, the proposed algorithm will improve the main financial performance indicators such as revenue per available room by an even bigger multiplier, depending on the hotel pricing policy. Because the room allocation process can be completely automated, the adoption of appropriate smart allocation algorithms represents a low-hanging fruit to be picked by efficient hotel managers. Originality/value To the best of the knowledge this is the first proposal of an optimal algorithm (with proof of optimality) for the considered problem.