Scalable Enterprise Systems: Procurement Problem Solving Modeling in Futuristic Enterprise Supply Chains Using Multi-Agents, Stochastic Programming and Game Theory

可扩展的企业系统：使用多代理、随机编程和博弈论解决未来企业供应链中的采购问题建模

• 批准号: 0075584
• 负责人: Soundar Kumara
• 金额: $ 9.36万
• 依托单位: Pennsylvania State Univ University Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-08-15 至 2003-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0075584&HistoricalAwards=false
• 关键词: Scalable; Enterprise; Systems; Procurement; Problem

Manufacturing companies need to make decisions regarding the choice of suppliers providing materials and the manufacturing sites for producing the final products. This decision-making problem in a supply chain is called the procurement problem. The solution to the procurement problem mainly consists of the least cost transportation between the suppliers and the manufacturing sites, and between the manufacturing sites and the customers. This research project tackles the procurement problem when the manufacturing company uses freight companies as third party transportation. The fundamental issues addressed are: (1) minimization of bid (transportation cost) for the manufacturing company, (2) maximization of payoff to the freight companies, (3) cost-optimal and cost-reliable estimation of the task-to-vehicle assignments by the freight companies, and (4) reliable fulfillment of the orders by the drivers of the vehicles. The research seeks to develop the problem solving model, communication mechanism and the solution process by using multi-agent paradigm, game theory and stochastic programming. The approach will be to use the driver's local behavior along with travel time and service time acquired in real-time through on board sensors for determining the bottlenecks on a feasible route, and announce collaboration requests for contingencies.This work will provide the basis for a scalable information intensive modeling and problem solving architecture for real-time procurement problem solving. Results of this research can be extended to build an integrated supply chain infrastructure (in real-time), in the e-business world.

制造公司需要就提供材料的供应商和生产最终产品的制造地点的选择做出决定。供应链中的这种决策问题称为采购问题。采购问题的解决主要包括供应商与生产基地之间以及生产基地与客户之间的最低成本运输。本研究针对制造企业采用货运公司作为第三方运输时的采购问题进行研究。所涉及的基本问题是：(1)最小化制造公司的投标(运输成本)，(2)最大化货运公司的收益，(3)货运公司对任务-车辆分配的成本最优和成本可靠的估计，以及(4)车辆司机可靠地履行订单。本研究试图运用多智能体范式、博弈论和随机规划理论，建立问题解决模型、沟通机制和解决过程。该方法将利用驾驶员的局部行为以及通过车载传感器实时获取的出行时间和服务时间来确定可行路线上的瓶颈，并发布应急协作请求，这将为可扩展的信息密集型建模和问题求解架构提供基础，用于实时解决采购问题。这项研究的成果可以扩展到在电子商务世界中建立一个集成的供应链基础设施(实时)。