SGER: Joint Optimization of Resource Allocation and Operational Decisions for Improving Random Yield

这项探索性研究（SGER）小额赠款将重点关注集成电路（ic）的制造和航空旅行的提供，作为此类制造和服务行业的核心例子。目标是建立数学模型，为确定如何在各种可用的提高产量的可能方法中分配稀缺资源提供基础。需要解决的关键问题包括：(1)不同的产量改变干预措施如何影响产量分布的参数？(2)收益分布的变化如何影响经营决策？(3)在收益率分布的哪个随机和/或参数顺序下，公司在经济上受益？(4)如何量化这种效益的大小？这些问题将使用运筹学的技术来回答，包括马尔可夫决策过程、随机/可变性排序和随机规划。生产过程的日益复杂以及在服务行业中创造和管理大量细分市场的能力提高了产量管理对制造商和服务提供商的重要性。有大量的文献讨论了在制造业环境中做出生产库存决策所必需的数学模型，或者类似地，在服务业环境中决定在特定的票价等级中提供多少产能，或者超额预订多少。本研究将通过开发通用模型来评估改变产量的干预措施，为两个不同的文献体之间提供一座桥梁。

This Small Grant for Exploratory Research (SGER) will focus on the manufacture of integrated circuits (ICs) and the provision of air travel as the central examples of such manufacturing and service industries. The goal is to develop mathematical models that provide a basis for determining how to allocate scarce resources among a variety of possible methods available to improve yield. Among the key questions to be addressed are: (1) How do different yield-altering interventions affect the parameters of the yield distribution? (2) How are operational decisions affected by changes in yield distributions? (3) Under which stochastic and/or parametric orders of yield distributions does a company benefit economically? (4) How can the magnitude of this benefit be quantified? These questions will be answered using techniques from operations research, including Markov decision processes, stochastic/variability orderings, and stochastic programming. The increasing complexity of production processes and the ability to create and manage a large number of market segments in service industries have served to elevate the importance of yield management to manufacturers and service providers alike.There is an extensive body of literature dealing with mathematical models necessary to make production-inventory decisions in the manufacturing context, or analogously, to decide how much capacity to make available in a particular fare-class, or how much to overbook, in the service industry context. This research will provide a bridge between two disparate bodies of literature by developing common models to evaluate yield-altering interventions.