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Article Navigation> JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY> 2015> 24(4): 526-533
XU Na, PENG Su-ping. Network topology optimization of supply chain information systems[J]. JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY, 2015, 24(4): 526-533. doi: 10.15918/j.jbit1004-0579.201524.0415
Citation: XU Na, PENG Su-ping. Network topology optimization of supply chain information systems[J].JOURNAL OF BEIJING INSTITUTE OF TECHNOLOGY, 2015, 24(4): 526-533.doi:10.15918/j.jbit1004-0579.201524.0415
shu

Network topology optimization of supply chain information systems

doi:10.15918/j.jbit1004-0579.201524.0415
  • 1.

    State Key Laboratory of Coal Resources and Safe Mining, China University of Mining and Technology, Beijing 100083, China;School of Business, Shandong Jianzhu University, Jinan 250101, China

  • 2.

    State Key Laboratory of Coal Resources and Safe Mining, China University of Mining and Technology, Beijing 100083, China

  • Received Date:2014-05-08
    Abstract
  • Network topology optimization has been widely researched. Since market competition has gradually developed into competition among the supply chain information systems, the network topology optimization of supply chain information systems has been in urgent need. However, the network topology optimization of supply chain information systems is still in its early stages and still has some challenges. So a description of typical seven network topologies for various supply chain information systems has been given. The generic characteristics of each network topology can be summarized. To analyze the optimization of network topology optimization of supply chain information systems, a numeric model has been established based on these general characteristics. A genetic algorithm is applied in the network topology optimization of supply chain information systems model to achieve the minimum cost and shortest path. Finally, our experiment results are provided to demonstrate the robustness and effectiveness of the proposed model.
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    • References (23)
  • [1]
    Yu Min, Nagurney Anna. Competitive food supply chain networks with application to fresh produce[J]. European Journal of Operational Research, 2013, 224(2): 273-282.
    [2]
    Liu Y H, Zhang Q, Lionel M Ni. Opportunity-based topology control in wireless sensor networks //Proceedings of the 28th International Conference on Distributed Computing Systems (ICDCS), Beijing, China, 2008.
    [3]
    Zhu Y, Huang M S, Chen S Y, et al. Cooperative energy spanners: energy-efficient topology control in cooperative ad hoc networks //Proceedings of IEEE International Conference on Computer Communications (INFOCOM), Shanghai, China, 2011.
    [4]
    Zhu Xiaojing. A recursive scalable topology for network on chip [J]. Chinese Journal of Computers, 2011, 34(5): 924-930.(in Chinese)
    [5]
    Fulya A, Mitsuo G, Lin L, et al. A genetic algorithm approach for multi-objective optimization of supply chain networks [J]. Computers and Industrial Engineering, 2006, 51(1): 196-215.
    [6]
    Pathak S D, Dilts D M, Biswas G. On the evolutionary dynamics of supply network topologies [J]. IEEE Transactions on Engineering Management. 2007, 54(4): 662-672.
    [7]
    Bernstein F, Federgruen A. Decentralized supply chains with competing retailers under demand uncertainty [J]. Management Science, 2005, 51(1): 18-29.
    [8]
    Kao D, Sabharwal A. Impact of network topology knowledge on fairness: a geometric approach //Proceedings of IEEE International Conference on Computer Communications (INFOCOM), Rio de Janeiro, 2009.
    [9]
    Morrice D J, Valdez R A, Jack J, et al.. Discrete event simulation in supply chain planning and inventory control at free scale semiconductor //Proceedings of the Winter Simulation Conference, 2005: 1718-1724.
    [10]
    Harland C M, Lamming R C, Zheng J, et al.. A taxonomy of supply networks [J]. Journal of Supply Chain Management, 2001, 37(4): 21-28.
    [11]
    Kong Fanrui, Li Chunwen. Dynamic key management scheme for wireless sensor network [J]. Journal of Software, 2010, 21(7): 1679-1691.
    [12]
    Salvatore S, Ilias L, Cecilia M, et al.. Understanding robustness of mobile networks through temporal network measures //Proceedings of IEEE International Conference on Computer Communications (INFOCOM), Shanghai, China, 2011.
    [13]
    Xu Jia, Feng Dengguo, Su Purui. Research on network-warning model based on dynamic peer-to-peer overlay hierarchy [J]. Journal o f Computer Research and Development, 2010, 47(9): 1574-1586.
    [14]
    Feng Tao, Li Hongtao, Yuan Zhanting, et al. Analysis method of robustness for topology of Bernoulli node model [J]. Acta Electronica Sinica, 2011, 39(7): 1673-1678.
    [15]
    Gilvan C Souza. Closed-loop supply chains: a critical review, and future research [J]. Decision Sciences, 2013, 44(1): 7-38.
    [16]
    Meade L, Sarkis J, Presley A. The theory and practice of Reverse Logistics [J]. International Journal of Logical System Management, 2007, 3: 56-84.
    [17]
    Min H, Ko C S, Ko H J. The spatial and temporal consolidation of returned products in a closed-loop supply chain network [J]. Computers & Industrial Engineering, 2006, 51(2): 309-320.
    [18]
    Qin Z F, Ji X Y. Logistics network design for product recovery in fuzzy environment [J]. European Journal of Operational Research, 2010, 202(2): 479-490.
    [19]
    Pishvaee M S, Farahani R Z, Dullaert W. A memetic algorithm for bi-objective integrated forward/reverse logistics network design [J]. Computer & Operations Research, 2010, 37(6): 1100-1112.
    [20]
    Lin Yun, Research on Construction and application of logistics service supply chain based automobile industry[D]. Chongqing: Chongqing University, 2011. (in Chinese)
    [21]
    Huang Ru. Study on automotive industry supply chain net collaborative model based on value net[D]. Shandong: Shandong University, 2009. (in Chinese)
    [22]
    Hu Ming. Research on the relationship of knowledge ambiguity, organizational absorptive capacity and knowledge transfer performance among hotel chain enterprises: knowledge transferred media as moderator variable[D]. Nanjing: Southeast University, 2009. (in Chinese)
    [23]
    Fang Na. Study on reorganization of cinema line system[D].Beijing: Beijing Jiaotong University,2009. (in Chinese)
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