Collaborative Research: Resource and Demand Allocation in Dynamic Environments

在这个项目中，我们专注于类的能力规划和资源分配问题，客户认为等待时间作为他们的主要关注点之一。 我们的目标是开发一种方法，联合最佳的能力规划和需求分配等问题。 该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：㈠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属性，即，产能规划和需求分配，包括客户对任何给定产能分配的个性化优化。 (iii)开发最佳的组合能力规划和需求分配算法，用于不同的设置。 该项目的预期成果包括理论见解以及动态环境下的能力规划和需求分配算法，这些算法将对制造经理、供应链经理、分销系统规划人员和服务运营经理有用。日益增长的全球竞争和信息技术的快速变化迫使公司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进行扩张，不仅是为了利用关税、劳动力和其他激励措施，而且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，都在广泛的地理区域内经营，并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会发生随机变化。 然而，单靠能力规划并不能保证这种全球多样化活动取得成功。在大多数现实情况下，即使客户可以由许多区域设施中的任何一个来服务，但是由于时间或成本考虑，一些客户可能对在特定设施处被服务具有自然的亲和力。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提供服务。这些区域间流动的总体影响可能会使一些设施的业绩恶化，而其他设施仍然没有得到充分利用。本项目通过考虑客户对公司分配决策的反应，为这些容量分配问题开发方法和理解。

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.