Collaborative Research: Resource and Demand Allocation in Dynamic Environments

在这个项目中，我们关注的是一类容量规划和资源分配问题，在这些问题中，客户将等待时间视为他们的主要关注点之一。目标是为这类问题制定一种联合最佳能力规划和需求分配的方法。这个项目的一个重要阶段是了解客户对容量分配规则的反应。该项目将通过以下步骤进行：(i)为联合能力规划和需求分配问题建立数学模型。（ii）确定问题的主要子组件的结构特性，即容量规划和需求分配，包括客户对任何给定容量分配的个人优化。制定最优的综合能力规划和需求分配算法，以供在各种情况下使用。该项目的预期产出包括理论见解以及动态环境中容量规划和需求分配的算法，这些将对制造经理、供应链经理、分销系统计划人员和服务运营经理有用。日益激烈的全球竞争和信息技术的快速变化迫使企业更加关注客户需求和系统响应能力；提供服务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都进行了扩张，不仅是为了利用关税、劳动力和其他激励措施，也是为了提供更好的客户服务。这些公司，无论是制造业还是服务业，都在一个广泛的地理区域内运作，并面临着一个动态的环境，在这个环境中，地理边界内和跨地理边界的需求都有随机变化。然而，仅靠能力规划并不能保证这种全球多样化投资的成功。在大多数实际情况下，即使客户可以由许多区域性设施中的任何一个提供服务，由于时间或成本方面的考虑，一些客户可能对在特定设施中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工作情况恶化，而另一些设施仍然得不到充分利用。该项目通过考虑客户对公司分配决策的反应，开发了解决这些容量分配问题的方法和理解。日益激烈的全球竞争和信息技术的快速变化迫使企业更加关注客户需求和系统响应能力；提供服务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都进行了扩张，不仅是为了利用关税、劳动力和其他激励措施，也是为了提供更好的客户服务。这些公司，无论是制造业还是服务业，都在一个广泛的地理区域内运作，并面临着一个动态的环境，在这个环境中，地理边界内和跨地理边界的需求都有随机变化。然而，仅靠能力规划并不能保证这种全球多样化投资的成功。在大多数实际情况下，即使客户可以由许多区域性设施中的任何一个提供服务，由于时间或成本方面的考虑，一些客户可能对在特定设施中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工作情况恶化，而另一些设施仍然得不到充分利用。该项目通过考虑客户对公司分配决策的反应，开发了解决这些容量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.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.