ESS: Dynamic and Stochastic Network Flow Models for Robust Revenue Optimization in Hotel Service Sector

ESS：酒店服务行业稳健收入优化的动态和随机网络流模型

• 批准号: 0223492
• 负责人: Sankaran Mahadevan
• 金额: --
• 依托单位: Vanderbilt University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-09-01 至 2006-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0223492&HistoricalAwards=false
• 关键词: ESS; Dynamic; Stochastic; Network; Flow

The research from this project is expected to produce significant methodological contributions to enhance revenue management practices through reservations control, in hotels and other service industries. In particular, to increase revenue potential, this project investigates the possibility of bridging the revenue gap between ideal revenue solution (if all requests were known ahead of time) and the current practice of maximizing expected revenue. To enhance the realism of demand assumptions, a statistical framework for modeling customer reservation decisions (consumption, cancellation, and duration) will be proposed. The project will also develop robust initial solutions by determining ideal revenue solutions for several demand request scenarios. Further, this optimal apriori solution will be updated over time as current reservation requests are revealed, thus accounting for discrepancies between forecasted and actual demands. The research findings and models will ultimately lead to the development of significantly improved and more robust revenue optimization practices in a variety of service industry networks, by synthesizing interdisciplinary principles from networks, reliability, algorithms, simulation, and forecasting to develop new models and tools for reservations control in the hotel industry. Benefits to various segments of the society include: (1) decision support tools for reservations managers; (2) improved revenues and revenue reliability for hotels and airlines; (3) health care service planning; and (3) reservations control for special events (e.g. concerts). In service sector industries such as airlines, hotels and rental car agencies, simple heuristic and empirical tools have been applied for reservations control. These current models are too restrictive in their assumptions, and do not account for the complexity of the revenue management problem. This project aims to develop methods for realistic modeling of the reservations problem, thus leading to increased revenue potential and robustness, through a network flow-based approach. To achieve these objectives, this project aims to: (1) develop a disaggregate framework to model the demand for reservations over time; (2) propose dynamic network models to obtain robust optimal solutions to the real-time reservations control problem; and (3) develop network-based models to maximize the robustness of revenues under uncertain arc costs (due to cancellation, no shows etc.). A graduate level course on 'Reliability and Optimization of Dynamic and Stochastic Infrastructure and Service Networks' will be developed to prepare leaders in research and practice in various service and infrastructure industries operating complex physical and/or virtual networks. The project will also aggressively recruit female and minority students to enhance the diversity of engineers in the service sector.

该项目的研究预计将产生重大的方法论贡献，以提高收入管理的做法，通过预订控制，在酒店和其他服务行业。 特别是，为了增加收入潜力，本项目研究了弥合理想收入解决方案（如果所有请求都提前知道）和最大化预期收入的现行做法之间的收入差距的可能性。为了提高现实的需求假设，建模客户预订决策（消费，取消，持续时间）的统计框架将被提出。该项目还将通过确定几个需求请求场景的理想收入解决方案来开发强大的初始解决方案。此外，随着当前预订请求被揭示，该最优先验解决方案将随时间更新，从而考虑预测需求与实际需求之间的差异。研究结果和模型将最终导致显着改善和更强大的收入优化实践在各种服务业网络的发展，通过综合跨学科的原则，从网络，可靠性，算法，模拟和预测，开发新的模型和工具，在酒店业的预订控制。 对社会各阶层的好处包括：（1）为预订经理提供决策支持工具;（2）提高酒店和航空公司的收入和收入可靠性;（3）医疗保健服务规划;以及（3）特殊活动（例如音乐会）的预订控制。在航空公司、酒店和汽车租赁机构等服务业行业中，简单的启发式和经验工具已应用于预订控制。 这些现行模式在假设方面限制太多，而且没有考虑到收入管理问题的复杂性。该项目旨在开发预订问题的现实建模方法，从而通过基于网络流的方法增加收入潜力和鲁棒性。为了实现这些目标，该项目旨在：（1）开发一个分解框架，以模拟随着时间的推移对预订的需求;（2）提出动态网络模型，以获得实时预订控制问题的鲁棒性最佳解决方案;（3）开发基于网络的模型，以最大限度地提高收入的鲁棒性在不确定的弧成本（由于取消，没有显示等）。 将开发一门研究生水平的课程“动态和随机基础设施和服务网络的可靠性和优化”，以培养各种服务和基础设施行业运营复杂物理和/或虚拟网络的研究和实践领导者。该项目还将积极招募女性和少数民族学生，以提高服务部门工程师的多样性。