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Modeling and Simulation for Effectiveness Evaluation of Dynamic Discrete Military Supply Chain Networks

Author

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  • Biao Xiong
  • Bixin Li
  • Rong Fan
  • Qingzhong Zhou
  • Wu Li

Abstract

The effectiveness of military supply chain networks is an important reference for logistics decision-making, and it is crucial to evaluate it scientifically and accurately. This paper highlights the problem from the perspective of dynamic and discrete networks. A topological structure model with the characteristics of dynamic and discreteness is used to describe the structure of military supply chain networks (MSCNs). In order to provide a platform for evaluating the effectiveness, simulation algorithms based on topological structure models for MSCNs are presented. Considering military and economic factors, evaluation metrics including supply capability and supply efficiency are proposed. By applying the model and algorithms to a POL supply network in a theater, we obtain the values of supply capability and efficiency metrics in a dynamic environment. We also identify an optimal solution from multiple feasible solutions to help decision-makers to make scientific and rational decisions by using exploratory analysis method. The results show that new evaluation metrics can capture important effectiveness requirements for military supply networks positively. We also find the proposed method in this paper can solve the problem of evaluating the effectiveness of dynamic and discrete network effectiveness evaluation in a feasible and effective manner.

Suggested Citation

  • Biao Xiong & Bixin Li & Rong Fan & Qingzhong Zhou & Wu Li, 2017. "Modeling and Simulation for Effectiveness Evaluation of Dynamic Discrete Military Supply Chain Networks," Complexity, Hindawi, vol. 2017, pages 1-9, October.
  • Handle: RePEc:hin:complx:6052037
    DOI: 10.1155/2017/6052037
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    References listed on IDEAS

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    1. Fan, Chin-Yuan & Fan, Pei-Shu & Chang, Pei-Chann, 2010. "A system dynamics modeling approach for a military weapon maintenance supply system," International Journal of Production Economics, Elsevier, vol. 128(2), pages 457-469, December.
    2. Réka Albert & Hawoong Jeong & Albert-László Barabási, 2000. "Error and attack tolerance of complex networks," Nature, Nature, vol. 406(6794), pages 378-382, July.
    3. Hao Li & Michiel C.J. Bliemer & Piet H.L. Bovy, 2009. "Reliability-based Dynamic Discrete Network Design with Stochastic Networks," Springer Books, in: William H. K. Lam & S. C. Wong & Hong K. Lo (ed.), Transportation and Traffic Theory 2009: Golden Jubilee, chapter 0, pages 651-673, Springer.
    4. Santoso, Tjendera & Ahmed, Shabbir & Goetschalckx, Marc & Shapiro, Alexander, 2005. "A stochastic programming approach for supply chain network design under uncertainty," European Journal of Operational Research, Elsevier, vol. 167(1), pages 96-115, November.
    5. Barabási, A.L & Jeong, H & Néda, Z & Ravasz, E & Schubert, A & Vicsek, T, 2002. "Evolution of the social network of scientific collaborations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 311(3), pages 590-614.
    6. Steven H. Strogatz, 2001. "Exploring complex networks," Nature, Nature, vol. 410(6825), pages 268-276, March.
    7. Barad, M. & Even Sapir, D., 2003. "Flexibility in logistic systems--modeling and performance evaluation," International Journal of Production Economics, Elsevier, vol. 85(2), pages 155-170, August.
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