Collaborative Research: Optimization Approach to Collaborative Games in Supply Chain Management

协作研究:供应链管理中协作博弈的优化方法

基本信息

  • 批准号:
    0654116
  • 负责人:
  • 金额:
    $ 5.94万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2007
  • 资助国家:
    美国
  • 起止时间:
    2007-08-01 至 2010-07-31
  • 项目状态:
    已结题

项目摘要

One of the most important issues in supply chain collaboration is how the participating firms share the cost and benefit. Such an issue can be naturally analyzed using concepts from the cooperative game theory. This project focuses on several fundamental cooperative supply chain games. A variety of relevant key issues for these cooperative games will be investigated, e.g., the existence of the core, computation of core allocations, sensitivity of core allocations to cost parameters, etc. These cooperative games are often multi-stage in nature, and involve demand/supply uncertainties and complex cost structures. These distinct features of supply chain games impose significant challenges. Studies on these games necessitate a variety of new and interesting optimization models. In response, advanced optimization techniques and algorithms need to be developed to analyze these cooperative games. If successful, this project will advance our knowledge in optimization, cooperative games, and supply chain management. The optimization techniques and algorithms developed from this project will be useful not only in analyzing cooperative supply chain games, but also in deepening our understanding of classical supply chain optimization models. Furthermore, this project will provide firms with guidelines to address the cost/benefit allocation issues in supply chain collaboration and ultimately help them improve the efficiency of their supply chains.
供应链合作中最重要的问题之一是参与企业如何分担成本和利益。这样的问题可以很自然地用合作博弈论的概念来分析。本项目主要研究几种基本的供应链合作博弈。将研究这些合作博弈的各种相关关键问题,例如,核心的存在,计算的核心分配,核心分配的敏感性,成本参数等。这些合作游戏往往是多阶段的性质,并涉及需求/供应的不确定性和复杂的成本结构。供应链游戏的这些独特特征带来了重大挑战。这些游戏的研究需要各种新的和有趣的优化模型。作为回应,需要开发先进的优化技术和算法来分析这些合作游戏。如果成功,这个项目将推进我们在优化,合作博弈和供应链管理方面的知识。本计画所发展之最佳化技术与演算法,不仅可应用于供应链合作博弈之分析,也可加深我们对经典供应链最佳化模型之了解。此外,该项目将为企业提供指导方针,以解决供应链合作中的成本/收益分配问题,并最终帮助他们提高供应链的效率。

项目成果

期刊论文数量(0)
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Jiawei Zhang其他文献

Designing a reductive hybrid membrane to selectively capture noble metallic ions during oil/water emulsion separation with further function enhancement
设计一种还原杂化膜,在油/水乳液分离过程中选择性捕获贵金属离子,并进一步增强功能
  • DOI:
    10.1039/c8ta01864b
  • 发表时间:
    2018
  • 期刊:
  • 影响因子:
    11.9
  • 作者:
    Lei Zhang;Xian-Hu Zha;Gui Zhang;Jincui Gu;Wei Zhang;Youju Huang;Jiawei Zhang;Tao Chen
  • 通讯作者:
    Tao Chen
Search for the semileptonic decay $D_s^+\to \pi^0e^+\nu_e$
搜索半轻衰变 $D_s^ o pi^0e^ u_e$
  • DOI:
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    0
  • 作者:
    B. C. M. Ablikim;M. Achasov;P. Adlarson;M. Albrecht;R. Aliberti;A. Amoroso;M. An;Q. An;X. Bai;Y. Bai;O. Bakina;R. Ferroli;I. Balossino;Y. Ban;V. Batozskaya;D. Becker;K. Begzsuren;N. Berger;M. Bertani;D. Bettoni;F. Bianchi;J. Bloms;A. Bortone;I. Boyko;R. Briere;A. Brueggemann;H. Cai;X. Cai;A. Calcaterra;G. Cao;N. Cao;S. Çetin;J. Chang;W. Chang;G. Chelkov;C. Chen;Chao Chen;G. Chen;Huifen. Chen;M. Chen;S. Chen;S. Chen;T. Chen;X. Chen;X. Chen;Y. Chen;Z. Chen;W. Cheng;X. Chu;G. Cibinetto;F. Cossio;J. Cui;H. Dai;J. Dai;A. Dbeyssi;R. Boer;D. Dedovich;Z. Deng;A. Denig;I. Denysenko;M. Destefanis;F. Mori;Y. Ding;J. Dong;L. Dong;M. Dong;X. Dong;S. Du;P. Egorov;Y. Fan;J. Fang;S. Fang;W. Fang;Y. Fang;R. Farinelli;L. Fava;F. Feldbauer;G. Felici;C. Feng;J. Feng;K. Fischer;M. Fritsch;C. Fritzsch;C. Fu;H. Gao;Y. Gao;Yan‐Yan Gao;S. Garbolino;I. Garzia;P. Ge;Z. Ge;C. Geng;E. Gersabeck;A. Gilman;K. Goetzen;L. Gong;W. Gong;W. Gradl;M. Greco;L. Gu;M. Gu;Y. Gu;C. Guan;A. Guo;L. Guo;R. Guo;Y. Guo;A. Guskov;T. Han;W. Han;X. Hao;F. Harris;K. He;K. He;F. Heinsius;C. Heinz;Y. Heng;C. Herold;M. Himmelreich;G. Hou;Y. Hou;Z. Hou;H. Hu;J. Hu;T. Hu;Y. Hu;G. Huang;K. Huang;L. Huang;X. Huang;Y. Huang;Z. Huang;T. Hussain;N. Husken;W. Imoehl;M. Irshad;J. Jackson;S. Jaeger;S. Janchiv;Q. Ji;Q. Ji;X. Ji;X. Ji;Y. Ji;Z. Jia;H. Jiang;S. Jiang;X. Jiang;Y. Jiang;J. Jiao;Z. Jiao;S. Jin;Y. Jin;M. Jing;T. Johansson;N. Kalantar;X. Kang;R. Kappert;M. Kavatsyuk;B. Ke;I. Keshk;A. Khoukaz;P. Kiese;R. Kiuchi;R. Kliemt;L. Koch;O. B. Kolcu;B. Kopf;M. Kuemmel;M. Kuessner;A. Kupsc;W. Kuhn;J. J. Lane;J. Lange;P. Larin;A. Lavania;L. Lavezzi;Z. Lei;H. Leithoff;M. Lellmann;T. Lenz;C. Li;C. Li;Cheng Li;D. Li;F. Li;G. Li;H. Li;H. Li;H. Li;H. Li;J. Li;J. Li;J. Li;Kenneth K. Li;L. Li;L. Li;Lei Li;M. Li;P. Li;S. Li;S. Li;T. Li;W. Li;W. Li;X. Li;X. Li;Xiaoyu Li;Z. Li;H. Liang;Y. Liang;Y. Liang;G. Liao;L. Liao;J. Libby;A. Limphirat;C. Lin;D. Lin;T. Lin;B. Liu;C. Liu;D. Liu;F. Liu;F. Liu;Feng. Liu;G. Liu;H. Liu;H. Liu;H. Liu;Huanhuan Liu;Huihui Liu;J. Liu;J. Liu;J. Liu;Li;Li;Li;Li;Lusheng Liu;M. Liu;Li;Q. Liu;S. Liu;T. Liu;W. Liu;W. Liu;X. Liu;Y. Liu;Y. Liu;Z. Liu;Z. Liu;X. Lou;F. Lu;H. Lu;J. Lu;X. Lu;Y. Lu;Y. Lu;Z. Lu;C. L. Luo;M. Luo;T. Luo;X. Luo;X. Lyu;Y. Lyu;F. Ma;H. Ma;Li Ma;M. Ma;Q. Ma;R. Ma;R. Ma;X. Ma;Y. Ma;F. Maas;M. Maggiora;S. Maldaner;S. Malde;Q. A. Malik;A. Mangoni;Y. Mao;Z. Mao;S. Marcello;Z. Meng;J. Messchendorp;G. Mezzadri;H. Miao;T. Min;R. Mitchell;X. Mo;N. Muchnoi;Y. Nefedov;F. Nerling;I. Nikolaev;Z. Ning;S. Nisar;Y. Niu;S. L. Olsen;Q. Ouyang;S. Pacetti;X. Pan;Y. Pan;A. Pathak;M. Pelizaeus;H. Peng;K. Peters;J. Ping;R. Ping;S. Plura;S. Pogodin;V. Prasad;F. Qi;H. Qi;H. Qi;M. Qi;T. Qi;S. Qian;W. B. Qian;Z. Qian;C. Qiao;J. Qin;L. Qin;X. Qin;X. Qin;Z. Qin;J. Qiu;S. Qu;K. H. Rashid;C. Redmer;K. Ren;A. Rivetti;V. Rodin;M. Rolo;G. Rong;C. Rosner;S. Ruan;H. Sang;A. Sarantsev;Y. Schelhaas;C. Schnier;K. Schoenning;M. Scodeggio;K. Shan;W. Shan;X. Shan;J. Shangguan;L. Shao;M. Shao;C. Shen;H. Shen;X. Shen;B. Shi;H. Shi;J. Shi;Q. Shi;R. Shi;X. Shi;X. Shi;J. Song;W. Song;Y. Song;S. Sosio;S. Spataro;F. Stieler;K. Su;P. Su;Y. Su;G. Sun;H. Sun;H. Sun;J. Sun;L. Sun;S. Sun;T. Sun;W. Sun;X. Sun;Y. Sun;Y. Sun;Z. Sun;Y. Tan;Y. Tan;C. Tang;G. Tang;J. Tang;L. Tao;Q. Tao;M. Tat;J. Teng;V. Thorén;W. Tian;Y. Tian;I. Uman;B. Wang;B. Wang;C. Wang;D. Wang;F. Wang;H. Wang;H. Wang;K. Wang;L. Wang;M. Wang;M. Wang;Meng Wang;S. Wang;T. Wang;T. Wang;W. Wang;W. Wang;W. Wang;X. Wang;X. Wang;X. L. Wang;Yu Wang;Y. Wang;Y. Wang;Y. Wang;Y. Wang;Yaqian Wang;Z. Wang;Z. Wang;Ziyi Wang;D. Wei;F. Weidner;S. Wen;D. White;U. Wiedner;G. Wilkinson;M. Wolke;L. Wollenberg;J. Wu;L. Wu;L. Wu;X. Wu;X. Wu;Y. Wu;Y. Wu;Z. Wu;L. Xia;T. Xiang;D. Xiao;G. Xiao;H. Xiao;S. Xiao;Y. Xiao;Z. Xiao;C. Xie;X. Xie;Y. Xie;Y. Xie;Y. Xie;Z. Xie;T. Xing;C. Xu;C. Xu;G. Xu;H. Xu;Q. Xu;X. Xu;Y. Xu;Z. Xu;F. Yan;L. Yan;W. Yan;W. Yan;H. Yang;H. Yang;Hang Yang;L. Yang;S. Yang;T. Yang;Y. Yang;Y. Yang;Yifan Yang;M. Ye;M. Ye;J. Yin;Z. You;B. Yu;C. Yu;G. Yu;T. Yu;C. Yuan;Lijuan Yuan;S. Yuan;X. Yuan;Y. Yuan;Z. Yuan;C. Yue;A. Zafar;F. Zeng;X. Zeng;Y. Zeng;Y. Zhan;A. Zhang;B. L. Zhang;B. Zhang;D. Zhang;G. Zhang;Houyu Zhang;Houyu Zhang;H. Zhang;J. Zhang;J. Zhang;J. Zhang;J. X. Zhang;J. Zhang;J. Zhang;Jianyu Zhang;Jiawei Zhang;L. Zhang;L. Zhang;Lei. Zhang;P. Zhang;Q. Zhang;Shuihan Zhang;Shulei Zhang;X. Zhang;X. Zhang;X. Zhang;Y. Zhang;Y. Zhang;Y. Zhang;Yan Zhang;Yao Zhang;Z. Zhang;Z. Zhang;G. Zhao;J. Zhao;J. Zhao;J. Zhao;Lei Zhao;Ling Zhao;M. Zhao;Q. Zhao;S. Zhao;Y. Zhao;Y. Zhao;Z. Zhao;A. Zhemchugov;B. Zheng;J. Zheng;Y. Zheng;B. Zhong;C. Zhong;X. Zhong;H. Zhou;L. Zhou;X. Zhou;X. Zhou;X. Zhou;X. Zhou;Yanlin Zhou;J. Zhu;K. Zhu;K. Zhu;L. Zhu;S. Zhu;S. Zhu;T. Zhu;W. Zhu;Y. Zhu;Z. Zhu;B. Zou;J. Zou
  • 通讯作者:
    J. Zou
Methoxylation and Direct Hydrogenative Coupling of Chloronitrobenzenes in Continuous Flow
连续流中氯硝基苯的甲氧基化和直接氢化偶联
  • DOI:
    10.1002/cjoc.201600606
  • 发表时间:
    2017-04
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Songjie Shi;Li Wan;Xiaoning Sun;Jiawei Zhang;Kai Guo
  • 通讯作者:
    Kai Guo
Uncertainty-aware multidimensional ensemble data visualization and exploration
不确定性感知多维集成数据可视化和探索
G5: A Universal GRAPH-BERT for Graph-to-Graph Transfer and Apocalypse Learning
  • DOI:
  • 发表时间:
    2020-06
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Jiawei Zhang
  • 通讯作者:
    Jiawei Zhang

Jiawei Zhang的其他文献

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{{ truncateString('Jiawei Zhang', 18)}}的其他基金

III: Medium: Collaborative Research: Self-Supervised Recommender System Learning with Application Specific Adaption
III:媒介:协作研究:具有特定应用适应性的自监督推荐系统学习
  • 批准号:
    2106972
  • 财政年份:
    2021
  • 资助金额:
    $ 5.94万
  • 项目类别:
    Standard Grant
III: Medium: Collaborative Research: An Extensible Heterogeneous Network Embedding Framework with Application Specific Adaptation
III:媒介:协作研究:具有特定应用适应能力的可扩展异构网络嵌入框架
  • 批准号:
    2152038
  • 财政年份:
    2021
  • 资助金额:
    $ 5.94万
  • 项目类别:
    Continuing Grant
III: Medium: Collaborative Research: Self-Supervised Recommender System Learning with Application Specific Adaption
III:媒介:协作研究:具有特定应用适应性的自监督推荐系统学习
  • 批准号:
    2202161
  • 财政年份:
    2021
  • 资助金额:
    $ 5.94万
  • 项目类别:
    Standard Grant
III: Medium: Collaborative Research: An Extensible Heterogeneous Network Embedding Framework with Application Specific Adaptation
III:媒介:协作研究:具有特定应用适应能力的可扩展异构网络嵌入框架
  • 批准号:
    1763365
  • 财政年份:
    2018
  • 资助金额:
    $ 5.94万
  • 项目类别:
    Continuing Grant

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