Collaborative Research: Resource and Demand Allocation in Dynamic Environments

合作研究：动态环境中的资源和需求分配

• 批准号: 0200406
• 负责人: Sridhar Seshadri
• 金额: $ 14.75万
• 依托单位: New York University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-08-15 至 2006-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0200406&HistoricalAwards=false
• 关键词: Collaborative; Research; Resource; Demand; Allocation

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.

在这个项目中，我们专注于能力计划和资源分配问题的类别，在这些问题中，客户将等待时间视为他们的主要问题之一。 目的是开发一种方法，以解决此类问题的联合最佳能力计划和需求分配。 该项目的一个重要阶段是了解对客户对容量分配规则的反应的理解。该项目将通过以下步骤进行：（i）为联合能力计划和需求分配问题开发数学模型。 （ii）确定问题主要子组件的结构性特性，即能力计划和需求分配，包括客户对任何给定能力分配的个人优化。 （iii）开发最佳的合并能力计划和需求分配算法，以在不同的环境中使用。 该项目的预期输出包括理论洞察力以及在动态环境中的容量计划和需求分配的算法，这些算法将用于制造经理，供应链经理，分销系统计划人员以及服务运营经理。进行全球竞争和信息技术的快速变化迫使公司对客户的需求和系统的需求更加关注；服务交付已成为改善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扩展了不仅利用关税，劳动力和其他激励措施，而且还提供了更好的客户服务。 这些公司（无论是制造还是服务）都在广泛的地理区域运营，并且面临着一个动态环境，在该环境中，地理边界内和跨地理边界内的需求发生了随机变化。 但是，仅产能计划并不能保证在这样的全球多元化企业中的成功。在大多数现实的情况下，即使客户可以由许多区域设施中的任何一个服务，但由于时间或成本的考虑，一些客户可能会在特定设施中提供自然亲和力。另一方面，随着一个位置的容量扩大，从其他地区吸引了更多的客户到该地点进行服务。这些区域间流的总体效果会使某些设施的性能恶化，而其他设施仍未得到充分利用。该项目通过考虑客户对公司的分配决策的反应，为这些容量分配问题开发方法和理解。