Collaborative Research: Resource and Demand Allocation in Dynamic Environments

在这个项目中，我们将重点放在容量规划和资源分配问题上，在这类问题中，客户将等待时间视为他们主要关心的问题之一。目标是为这类问题制定一种联合最优能力规划和需求分配的方法。该项目的一个重要阶段是了解客户对运力分配规则的反应。该项目将通过以下步骤进行：(I)建立联合能力规划和需求分配问题的数学模型。(Ii)确定问题的主要子组成部分的结构属性，即能力规划和需求分配，包括客户对任何给定能力分配的个体优化。(3)制定最优组合能力规划和需求分配算法，以便在不同情况下使用。该项目的预期输出包括动态环境中产能规划和需求分配的理论见解和算法，将对制造经理、供应链经理、分销系统规划者和服务运营经理有用。日益激烈的全球竞争和快速的信息技术变化正迫使公司更加关注客户需求和系统响应能力；服务交付已成为提高公司竞争地位的关键因素。许多美国公司在国内和国际上扩张，不仅是为了利用关税、劳动力和其他激励措施，还为了提供更好的客户服务。这些公司，包括制造业和服务业，在广泛的地理区域内运营，面临着一个动态的环境，在这个环境中，在地理边界内和跨地理边界的需求都有随机变化。然而，仅靠产能规划并不能保证这种全球多元化投资的成功。在大多数现实情况下，即使客户可以通过许多地区性设施中的任何一个提供服务，但出于时间或成本考虑，一些客户可能对在特定设施获得服务具有天然的亲和力。另一方面，随着一个地点的容量扩大，更多的客户从其他地区吸引到这个地点服务。这些区域间流动的总体影响可能会使一些设施的表现恶化，而另一些设施仍未得到充分利用。该项目通过考虑客户对公司分配决策的反应，制定了解决这些产能分配问题的方法和理解。

In this project we focus on the class of capacity planning and resource allocation problems in which customers view waiting times as one of their major concerns. The objective is to develop a methodology for joint optimal capacity planning and demand allocation for such problems. An important phase in this project is to develop an understanding of customer reactions to capacity allocation rules. The project will be conducted through the following steps: (i) Develop mathematical models for the joint capacity planning and demand allocation problem. (ii) Determine structural properties of the main sub-components of the problem, viz., capacity planning and demand allocation, including customer's individual optimization for any given capacity allocation. (iii) Develop optimal combined capacity planning and demand allocation algorithms for use in diverse settings. The expected output of this project includes theoretical insight as well as algorithms for capacity planning and demand allocation in dynamic environments that will be of use to manufacturing managers, supply chain managers, distribution systems planners, and service operations managers.Growing global competition and rapid changes in information technology are forcing companies to pay more attention to customer needs and system responsiveness; service delivery has become a key factor in improving a company's competitive position. Many US companies have expanded both nationally and internationally not only to take advantage of tariff, labor and other incentives but also to provide better customer service. These firms, both manufacturing and service, operate over a wide-spread geographic area and face a dynamic environment in which there are random changes in demand within and across geographic boundaries. However, capacity planning alone will not guarantee success in such global diversification ventures. In most realistic situations, even though customers can be served by any one of many regional facilities, some customers may have a natural affinity for being served at a specific facility because of time or cost considerations. On the other hand, as the capacity at one location is expanded, more customers are attracted from other regions to this location for service. The overall effect of these inter-region flows can deteriorate the performance at some facilities while other facilities remain underutilized. This project develops methodologies and understanding for these capacity allocation problems by taking into consideration how customers react to the firm's allocation decisions.