Modeling and simulation for effectiveness evaluation of dynamic discrete military supply chain networks.

*(English)*Zbl 1377.93102Summary: The effectiveness of Military Supply Chain Networks (MSCNs) 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 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.

##### MSC:

93C55 | Discrete-time control/observation systems |

90B06 | Transportation, logistics and supply chain management |

90B15 | Stochastic network models in operations research |

PDF
BibTeX
XML
Cite

\textit{B. Xiong} et al., Complexity 2017, Article ID 6052037, 9 p. (2017; Zbl 1377.93102)

Full Text:
DOI

##### References:

[1] | Strogatz, S. H., Exploring complex networks, Nature, 410, 6825, 268-276, (2001) · Zbl 1370.90052 |

[2] | Gershenson, C.; Prokopenko, M., Complex networks, Artificial Life, 17, 4, 259-261, (2011) |

[3] | Barabási, A. L.; Jeong, H.; Néda, Z.; Ravasz, E.; Schubert, A.; Vicsek, T., Evolution of the social network of scientific collaborations, Physica A: Statistical Mechanics and its Applications, 311, 3-4, 590-614, (2002) · Zbl 0996.91086 |

[4] | Boccaletti, S.; Latora, V.; Moreno, Y.; Chavez, M.; Hwang, D.-U., Complex networks: structure and dynamics, Physics Reports, 424, 4-5, 175-308, (2006) · Zbl 1371.82002 |

[5] | Albert, R.; Jeong, H.; Barabasi, A.-L., Error and attack tolerance of complex networks, Nature, 406, 4, 378-382, (2000) |

[6] | Ravasz, E.; Barabási, A., Hierarchical organization in complex networks, Physical Review E, 67, 2, (2003) · Zbl 1151.91744 |

[7] | Li, H.; Bliemer, M. C. J.; Bovy, P. H. L.; Lam, W. H. K.; Wong, S. C.; Lo, H. K., Reliability-based dynamic discrete network design with stochastic networks, Transportation and Traffic Theory, 651-673, (2009) |

[8] | Barad, M.; Sapir, D. E., Flexibility in logistic systems—modeling and performance evaluation, International Journal of Production Economics, 85, 2, 155-170, (2003) |

[9] | Ng, Y. S., Optimizing A Military Supply Chain in The Presence of Random Non-Stationary Demands, (2003) |

[10] | Chai, Y.; Hu, H., Military supply chain management strategies under demand disruption, Proceedings of the IEEE International Conference on Automation and Logistics (ICAL ’08) |

[11] | Thomas, M. U., Supply chain reliability for contingency operations, Proceedings of the Annual Reliability and Maintainability Symposium, Institute of Electrical and Electronics Engineers |

[12] | Thadakamalla, H. P.; Raghavan, U. N.; Kumara, S.; Albert, R., Survivability of multiagent-based supply networks: a topological perspective, IEEE Intelligent Systems, 19, 5, 24-31, (2004) |

[13] | Zhao, K.; Kumar, A.; Harrison, T. P.; Yen, J., Analyzing the resilience of complex supply network topologies against random and targeted Disruptions, IEEE Systems Journal, 5, 1, 28-39, (2011) |

[14] | Wang, N.; Lu, J.-C.; Kvam, P., Reliability modeling in spatially distributed logistics systems, IEEE Transactions on Reliability, 55, 3, 525-534, (2006) |

[15] | Zhou, Q.; Xiong, B.; Li, B.; Huang, J.; Lu, S., Analysing the resilience of military supply network and simulation against disruptions, International Journal of Engineering Systems Modelling and Simulation, 8, 3, 195-204, (2016) |

[16] | Klimov, R.; Merkuryev, Y., Simulation model for supply chain reliability evaluation, Technological and Economic Development of Economy, 14, 3, 300-311, (2008) |

[17] | Shariat-Mohaymany, A.; Babaei, M., An approximate reliability evaluation method for improving transportation network performance, Transport, 25, 2, 193-202, (2010) |

[18] | Yeh, W.-C., A hybrid heuristic algorithm for the multistage supply chain network problem, International Journal of Advanced Manufacturing Technology, 26, 5-6, 675-685, (2005) |

[19] | Santoso, T.; Ahmed, S.; Goetschalckx, M.; Shapiro, A., A stochastic programming approach for supply chain network design under uncertainty, European Journal of Operational Research, 167, 1, 96-115, (2005) · Zbl 1075.90010 |

[20] | Zhang, S.; Lee, C. K. M.; Wu, K.; Choy, K. L., Multi-objective optimization for sustainable supply chain network design considering multiple distribution channels, Expert Systems with Applications, 65, 87-99, (2016) |

[21] | Pathak, S. D.; Dilts, D. M.; Biswas, G., On the evolutionary dynamics of supply network topologies, IEEE Transactions on Engineering Management, 54, 4, 662-672, (2007) |

[22] | Hu, X. F.; Zhang, Y.; Li, R. J.; Yang, J. Y., Capability evaluating problem of networking SoS, Systems Engineering Theory & Practice, 35, 5, 1317-1323, (2015) |

[23] | Foulliaron, J.; Bouillaut, L.; Barros, A.; Aknin, P., Dynamic Bayesian Networks for reliability analysis: from a Markovian point of view to semi-Markovian approaches, IFAC-PapersOnLine, 28, 21, 694-700, (2015) |

[24] | Fan, C.-Y.; Fan, P.-S.; Chang, P.-C., A system dynamics modeling approach for a military weapon maintenance supply system, International Journal of Production Economics, 128, 2, 457-469, (2010) |

[25] | Oliveira, J. B.; Lima, R. S.; Montevechi, J. A. B., Perspectives and relationships in Supply Chain Simulation: a systematic literature review, Simulation Modelling Practice and Theory, 62, 166-191, (2016) |

This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.