SBIR Phase I: Revenue Management in a dynamic and stochastic network environment

这个小型企业创新研究(SBIR)第一阶段项目将调查收入管理(RM)系统的库存分配。作为一种接近供应/需求概念的新方法，RM可以被最好地理解为通过有效利用可用的易腐烂资源来实现收入最大化的一组行动。第一阶段将：(I)设计一个高度优化的动态库存分配算法，该算法可以很容易地集成到一个更通用的RM框架中；(Ii)建立一个实现该算法的决策软件的原型。实验策略将基于包含问题的动态、随机和网络特征的通用RM模型。第一阶段将使用最先进的数学(近似动态规划和随机数学规划)和数据库工具。这项工作有望在不同的行业中进行潜在的商业应用，从交通和酒店业到电信、医疗保健、法律服务、娱乐和政府机构。新方法预计将比最先进的RM系统改进2%-3%，这将转化为收入的大幅增加，特别是在竞争激烈和高度受限的领域。

This Small Business Innovation Research (SBIR) Phase I project will investigate the inventory allocation of revenue management (RM) systems. As a new way of approaching the supply/demand concept, RM can be best understood as the set of actions leading to revenue maximization by efficiently utilizing the available perishable resources. Phase I will: (i) devise a highly optimized dynamic inventory allocation algorithm that can be easily integrated in a more general RM framework; and (ii) build a prototype of decision making software implementing the algorithm. The experimental policy will be based on a general RM model that encompasses the dynamic, stochastic, and network characteristics of the problem. Phase I will use state-of-the-art mathematical (approximate dynamic programming and stochastic mathematical programming) and database tools.Potential commercial applications of the work are expected in a diverse set of industries, ranging from the transportation and hospitality industries to telecommunications, health care, legal services, entertainment, and government organizations. The new approach is expected to lead to 2%-3% improvements over state-of-the-art RM systems, and this will translate to considerable increases in revenue especially in highly competitive and highly constrained arenas.