IDEA: Integrated Decomposition for Enterprise Analysis

IDEA：企业分析的集成分解

• 批准号: 0649511
• 负责人: Julia Higle
• 金额: --
• 依托单位: Ohio State University Research Foundation -DO NOT USE
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-08-01 至 2008-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0649511&HistoricalAwards=false
• 关键词: IDEA; Integrated; Decomposition; Enterprise; Analysis

This project identifies a new class of stochastic programs referred to as"Distributed Stochastic Programs," and develops computational approachesfor their solution. The methodology to be studied involves a marriage of the"Lagrangean Decomposition" method of Guignard and Kim with the "StochasticDecomposition" methods of Higle and Sen. The primary motivation is the study ofintegrated models and solution methods for enterprise-based decision making under uncertainty. An enterprise-based model is one that couples a variety of component problems that are associated with different entities within the enterprise. Of necessity these component problems, which will typically reflect operational concerns,are finely detailed. Their individual solutions often require highly specialized computational approaches that challenge current computing resources. As a result, their direct incorporation within anenterprise-based model would likely lead to a model that greatly exceedscurrent computational capabilities. To remedy this situation, thisproject advocates the use of surrogate models of the component problemsthat reflect the uncertainty associated with the day-to-day operations,and are combined in a manner that permits guidance for strategic decisions. A primary goal of this project is the development of solution methods for the resulting class of problems based on decomposition schemes that exploit the general structure of the enterprise model.Over the past few years, the need to incorporate uncertaintywithin complex business environments has become increasinglyobvious. Many firms have invested a great deal of time andresources in developing models that can be used to assist withoperational decision making. For example, airlines typically usesophisticated models to assist with their air fleet assignments, crewscheduling, maintenance schedules, etc. In addition to thesetypes of operational decisions, firms also undertake strategic, orlong-term, decisions, such as when an airline determineswhat markets it will serve. In general, these strategic decisionsimpact the operational decisions, although neither this impact nor the uncertainty associated with day-to-day operational decisions istypically captured within the enterprise's strategic decision model. This project involves an exploration of integrated models and solution methods for enterprise-based decision making under uncertainty.

这个项目确定了一类新的随机程序，称为“分布式随机程序”，并开发了计算方法，为他们的解决方案。 要研究的方法涉及的婚姻的“拉格朗日分解”方法的Guignard和金与“随机分解”方法的Higle和森的主要动机是研究ofintegrated模型和解决方案的方法，为企业为基础的决策下的不确定性。 一个基于企业的模型是一个耦合各种组件问题的模型，这些问题与企业内的不同实体相关联。这些组件问题通常反映了操作方面的问题，因此必须详细说明。 他们各自的解决方案往往需要高度专业化的计算方法，挑战当前的计算资源。 因此，将它们直接合并到基于企业的模型中可能会导致一个大大提高当前计算能力的模型。 为了纠正这种情况，本项目主张使用替代模型的组件problems，反映了与日常操作的不确定性，并结合在一起的方式，允许指导战略决策。 该项目的主要目标是开发基于分解方案的问题解决方法，这些分解方案利用了企业模型的一般结构。在过去的几年里，在复杂的商业环境中纳入不确定性的需求变得越来越明显。 许多公司已经投入了大量的时间和资源来开发可以用来帮助运营决策的模型。 例如，航空公司通常使用复杂的模型来帮助他们的机队分配，机组人员调度，维护计划等。除了这些类型的运营决策，公司还承担战略，或长期的决策，如航空公司何时决定它将服务于什么市场。 一般来说，这些战略决策会影响运营决策，尽管这种影响和与企业战略决策模型中典型地捕获的日常运营决策相关的不确定性都没有。 本计画探讨不确定性下企业决策之整合模式与求解方法。