This study introduces the methods of supply chain inventory management into the cluster supply chains and proposes the implementation of supply chain inventory management strategies under this circumstance. First, we analyze the system behavior patterns of the co-operation planning, forecasting and replenishment (CPFR), vendor-managed inventory (VMI), and jointly managed inventory (JMI) models of cluster supply chains. Therefore, we establish the inventory management models of CPFR, VMI and JMI in cluster supply chains. These models are simulated by VENSIM software. The simulation results show that compared with those in the VMI and JMI models, the inventory fluctuations of manufacturers, wholesalers and retailers in the CPFR model correspond; the total inventory is reduced while its stability is greatly improved. Therefore, the application of CPFR in cluster supply chains can effectively restrain the bullwhip effect, reduce the inventory and improve the efficiency of the entire supply chain.
Accepté le :
DOI : 10.1051/ro/2016054
Mots clés : Inventory management, cluster supply chains, system dynamics, CPFR, VMI
@article{RO_2017__51_3_763_0,
author = {Yan, Bo and Wu, Jiwen and Liu, Lifeng and Chen, Qiuqing},
title = {Inventory management models in cluster supply chains based on system dynamics},
journal = {RAIRO - Operations Research - Recherche Op\'erationnelle},
pages = {763--778},
publisher = {EDP-Sciences},
volume = {51},
number = {3},
year = {2017},
doi = {10.1051/ro/2016054},
mrnumber = {3880524},
zbl = {1384.90008},
language = {en},
url = {http://www.numdam.org/articles/10.1051/ro/2016054/}
}
TY - JOUR AU - Yan, Bo AU - Wu, Jiwen AU - Liu, Lifeng AU - Chen, Qiuqing TI - Inventory management models in cluster supply chains based on system dynamics JO - RAIRO - Operations Research - Recherche Opérationnelle PY - 2017 SP - 763 EP - 778 VL - 51 IS - 3 PB - EDP-Sciences UR - http://www.numdam.org/articles/10.1051/ro/2016054/ DO - 10.1051/ro/2016054 LA - en ID - RO_2017__51_3_763_0 ER -
%0 Journal Article %A Yan, Bo %A Wu, Jiwen %A Liu, Lifeng %A Chen, Qiuqing %T Inventory management models in cluster supply chains based on system dynamics %J RAIRO - Operations Research - Recherche Opérationnelle %D 2017 %P 763-778 %V 51 %N 3 %I EDP-Sciences %U http://www.numdam.org/articles/10.1051/ro/2016054/ %R 10.1051/ro/2016054 %G en %F RO_2017__51_3_763_0
Yan, Bo; Wu, Jiwen; Liu, Lifeng; Chen, Qiuqing. Inventory management models in cluster supply chains based on system dynamics. RAIRO - Operations Research - Recherche Opérationnelle, Tome 51 (2017) no. 3, pp. 763-778. doi : 10.1051/ro/2016054. http://www.numdam.org/articles/10.1051/ro/2016054/
, and , Impact of information sharing and lead time on bullwhip effect and on-hand inventory. Eur. J. Oper. Res. 192 (2009) 576–593. | DOI | MR | Zbl
, , , and , Role of feed-in tariff policy in promoting solar photovoltaic investments in Malaysia: A system dynamics approach. Energy 84 (2015) 808–815. | DOI
, and , Agent based modeling and simulation: an informatics perspective. J. Artif. Soc. Soc. Simul. 12 (2009) 4.
and , Demand forecasting and sharing strategies to reduce fluctuations and the bullwhip effect in supply chains. J. Oper. Res. Soc. 62 (2011) 458–473. | DOI
A. Borshchev, From System Dynamics and Discrete Event to Practical Agent Based Modeling: Reasons, Techniques, Tools. International Conference of the System Dynamics Society (2010).
and , Cluster building and logistics network integration of local food supply chain. Biosyst. Eng. 108 (2011) 293–302. | DOI
, and , Inventory policies and information sharing in multi-echelon supply chains. Prod. Plan. Control 22 (2011) 649–659. | DOI
and , On the bullwhip avoidance phase: supply chain collaboration and order smoothing. Int. J. Prod. Res. 48 (2010) 6739–6776. | DOI | Zbl
, and , An IT-enabled supply chain model: a simulation study. Int. J. Syst. Sci. 45 (2014) 2327–2341. | DOI | Zbl
S. Cannella, M. LópezCampos, R. Dominguez, J. Ashayeri and P.A. Miranda, A simulation model of a coordinated decentralized supply chain. Int. Trans. Oper. Res. (2015). | MR
, , and , The bullwhip effect – Impact of stochastic lead time, information quality, and information sharing: A simulation study. Prod. Oper. Manage. 13 (2004) 340–353. | DOI
, , and , On the bullwhip avoidance phase: the Synchronised Supply. Eur. J. Oper. Res. 22 (2012) 49–63. | DOI | Zbl
, and , On bullwhip-limiting strategies in divergent supply chain networks. Comput. Ind. Eng. 73 (2014) 85–95. | DOI
, Industrial Dynamics. J. Oper. Res. Soc. 48 (1997) 1037–1041. | DOI
and , System dynamics model for optimizing the recycling and collection of waste material in a closed-loop supply chain. Simul. Model. Pract. Theory 53 (2015) 88–102. | DOI
, , and , Multibody system dynamics simulator for process simulation of ships and offshore plants in shipyards. Adv. Eng. Softw. 85 (2015) 12–25. | DOI
, and , Evaluation of sustainable policy in urban transportation using system dynamics and world cities data: a case study in Isfahan. Cities 45 (2014) 104–115. | DOI
, and , The impact of replenishment parameters and information sharing on the Bullwhip effect: a computational study. Comput. Oper. Res. 35 (2008) 3657–3670. | DOI | Zbl
, and , Information distortion in a supply chain: the bullwhip effect. Management Science 50 (1997) 1875–1886. | DOI | Zbl
, and , From waste to value – a system dynamics model for strategic decision-making in closed-loop supply chains. Int. J. Prod. Res. 51 (2013) 4105–4116. | DOI
and , Participatory modeling and analysis for sustainable forest management: overview of soft system dynamics models and applications. Forest Policy Econ. 9 (2006) 179–196. | DOI
P. Milling and N. Schieritz, Modeling the Forest or Modeling the Trees: A Comparison of System Dynamics and Agent-Based Simulation (2003).
and , A system dynamics model for information security management. Inf. Manage. 52 (2015) 123–134. | DOI
and , A supply network optimisation with functional clustering of industrial resources. J. Cleaner Prod. 71 (2014) 87–97. | DOI
, System Dynamics modelling of a production and inventory system for remanufacturing to evaluate system improvement strategies. Int. J. Prod. Econ. 144 (2013) 189–199. | DOI
, H. Evers and Yaniasih, Knowledge flow in the academia-industry collaboration or supply chain linkage? case study of the automotive industries in the jababeka cluster. Procedia – Soc. Behavior. Sci. 52 (2012) 62–71. | DOI
, , , , and , Optimal configuration of cluster supply chains with augmented Lagrange coordination. Comput. Ind. Eng. 84 (2015) 43–55. | DOI
N. Schieritz and A. Ler, Emergent Structures in Supply Chains “A Study Integrating Agent-Based and System Dynamics Modeling”. Hawaii International Conference on System Sciences. IEEE Computer Society. (2003) 94a.
and , The Application of Discrete Event Simulation and System Dynamics in the Logistics and Supply Chain Context. Decis. Support Syst. 52 (2012) 802–815. | DOI
, and , Impact of information exchange on supplier forecasting performance. Omega 40 (2010) 738–747. | DOI
and , Eco-cities: An integrated system dynamics framework and a concise research taxonomy. Sustain. Cities Soc. 17 (2015) 1–14. | DOI
and , Buyer-supplier transport access measures for industry clusters. J. Appl. Res. Technol. 12 (2014) 839–849. | DOI
and , An extended kalman filter for collaborative supply chains. Int. J. Prod. Res. 42 (2007) 2457–2475. | DOI | Zbl
, , , , and , A study of the diffusion of agility and cluster competitiveness in the oil and gas supply chains. Int. J. Prod. Econ. 147 (2014) 498–513. | DOI
and , Modelling of cluster supply network with cascading failure spread and its vulnerability analysis. Int. J. Prod. Res. 52 (2014) 6938–6953. | DOI
, and , Coordination game model of co-opetition relationship on cluster supply chains. J. Syst. Eng. Electron. 19 (2008) 499–506. | DOI
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