Coordinating Multiple Decision Makers in a Service Environment
在服务环境中协调多个决策者
基本信息
- 批准号:1031637
- 负责人:
- 金额:$ 30.4万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2010
- 资助国家:美国
- 起止时间:2010-10-01 至 2014-09-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The goal of this project is to develop methods for controlling stochastic dynamic systems that are populated with multiple interacting agents endowed with private information, different performance objectives and different risk attitudes. The research will develop mechanisms based on revenue sharing/transfer price contracts as a way to modify agent incentives and to induce decentralized decisions that are also centrally optimal. Methods for computing both optimal as well as suboptimal revenue sharing contracts will be developed using ideas from approximate dynamic programming. Applications to multi-agent systems of interest to operations research and management science including the coordination of airline alliances, multi-agent risk management, and multi-agent service systems will be studied.If successful, the results of this research will lead to a greater understanding of the mechanisms that can be used to coordinate interacting decentralized agents in stochastic dynamic systems. It will also lead to the development of efficient methods for computing optimal and/or suboptimal revenue sharing contracts that are used to coordinate these decision makers. These results will provide guidelines for organizing and managing complex systems that are populated with multiple agents.
该项目的目标是开发控制随机动态系统的方法,该系统由多个具有私人信息,不同性能目标和不同风险态度的交互代理填充。这项研究将开发基于收入分享/转让价格合同的机制,作为修改代理激励和诱导分散决策的一种方式,这些决策也是集中优化的。计算最优和次优收入共享合同的方法将使用近似动态规划的思想。本课程将研究多代理系统在运筹学和管理科学中的应用,包括航空公司联盟的协调、多代理风险管理和多代理服务系统,如果成功的话,本研究的结果将使我们更好地理解在随机动态系统中用于协调相互作用的分散代理的机制。它还将导致开发用于计算用于协调这些决策者的最优和/或次优收入共享合同的有效方法。这些结果将为组织和管理由多个代理填充的复杂系统提供指导。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Andrew Lim其他文献
Learning variable ordering heuristics for solving Constraint Satisfaction Problems
学习变量排序启发法来解决约束满足问题
- DOI:
10.1016/j.engappai.2021.104603 - 发表时间:
2021 - 期刊:
- 影响因子:8
- 作者:
Wen Song;Zhiguang Cao;Jie Zhang;Chi Xu;Andrew Lim - 通讯作者:
Andrew Lim
The race is not to the swift
比赛不在于速度快
- DOI:
10.1046/j.1468-4004.2003.45112.x - 发表时间:
2004 - 期刊:
- 影响因子:0.8
- 作者:
M. K. Pickett;Andrew Lim - 通讯作者:
Andrew Lim
Capturing Expert Arguments from Medical Adjudication Discussions in a Machine-readable Format
以机器可读的格式从医学裁决讨论中获取专家观点
- DOI:
- 发表时间:
2019 - 期刊:
- 影响因子:0
- 作者:
M. Schaekermann;Graeme Beaton;Minahz Habib;Andrew Lim;K. Larson;E. Law - 通讯作者:
E. Law
An iterated construction approach with dynamic prioritization for solving the container loading problems
一种解决集装箱装载问题的动态优先级迭代构建方法
- DOI:
10.1016/j.eswa.2011.09.103 - 发表时间:
2012-03 - 期刊:
- 影响因子:8.5
- 作者:
Andrew Lim;Hong Ma;Jing Xu;Xingwen Zhang - 通讯作者:
Xingwen Zhang
Robust data-driven vehicle routing with time windows
- DOI:
https://doi.org/10.1287/opre.2020.2043 - 发表时间:
2021 - 期刊:
- 影响因子:
- 作者:
章宇;Zhenzhen Zhang;Andrew Lim;Melvyn Sim - 通讯作者:
Melvyn Sim
Andrew Lim的其他文献
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{{ truncateString('Andrew Lim', 18)}}的其他基金
Objective Operational Learning and Applications
客观操作学习与应用
- 批准号:
1201085 - 财政年份:2012
- 资助金额:
$ 30.4万 - 项目类别:
Standard Grant
Stochastic Optimization with Model Uncertainty and Learning
具有模型不确定性和学习的随机优化
- 批准号:
0500503 - 财政年份:2005
- 资助金额:
$ 30.4万 - 项目类别:
Continuing Grant
SBIR Phase I: FileSafe: Policy-Driven Storage Virtualization for Online Data Backup and Recovery
SBIR 第一阶段:FileSafe:用于在线数据备份和恢复的策略驱动存储虚拟化
- 批准号:
0441700 - 财政年份:2005
- 资助金额:
$ 30.4万 - 项目类别:
Standard Grant
CAREER: Stochastic Control Problems in Financial Engineering
职业:金融工程中的随机控制问题
- 批准号:
0348746 - 财政年份:2004
- 资助金额:
$ 30.4万 - 项目类别:
Continuing Grant
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