Abstract
The industry and retail chain use a huge number of low cost assets such as pallets, crates, plastic boxes… Until now the lack of affordable technology, in comparison with the cost of a single asset, stopped efforts to manage them in open loop supply chain (where the assets are not coming back to the sender after usage). As part of a project to implement an affordable and efficient communication technology and to publish the information from the logistics assets used in Fast Moving Consumer Goods’ supply chains, we demonstrate with a simulation optimization approach the benefit of knowing the position of the assets. The published events from the logistics support are used to optimize their repositioning. A specific simulation optimization model is presented and the results are commented.
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References
Ballot, E., Montreuil, B., Meller, R.D.: The Physical Internet: The Network of Logistics Networks, 232 p. La documentation Française (2014)
Carson, Y., Maria, A.: Simulation optimization: methods and applications. In: 29th Conference on Winter Simulation, pp. 118–126. IEEE Computer Society (1997)
Figueira, G., Almada-Lobo, B.: Hybrid simulation-optimization methods: a taxonomy and discussion. Simul. Model. Pract. Theory 46, 118–134 (2014)
Gaubert, E., Guerrero, D.: Les enquêtes Chargeur: l’observation de la demande de transport de marchandises au service des politiques publiques. IFSTTAR (2013)
GS1 Global Traceability Standard: Business Process and System Requirements for Full Chain Traceability. Issue 1.1.0 (2009)
Le Roch, Y., Ballot, E.: Internet (s) des objets logistiques et modèles d’affaires. Réalités industrielles 2, 97–101 (2013)
Lin, Y.-H., Meller, R.D., Ellis, K.P., Thomas, L.M., Lombardi, B.J.: A decomposition-based approach for the selection of standardized modular containers. Int. J. Prod. Res. 52(15), 4660–4672 (2014). doi:10.1080/00207543.2014.883468
Markt, P.L., Mayer, M.H.: WITNESS simulation software: a flexible suite of simulation tools, pp. 711–717. In: 29th Conference on Winter Simulation. IEEE Computer Society (1997)
Montreuil, B.: Toward a physical internet: meeting the global logistics sustainability grand challenge. Logistics Res. 3(2–3), 71–87 (2011). doi:10.1007/s12159-011-0045-x
Pan, S., Ballot, E., Fontane, F.: The reduction of greenhouse gas emissions from freight transport by pooling supply chains. Int. J. Prod. Econ. 143(1), 86–94 (2013). doi:http://dx.doi.org/10.1016/j.ijpe.2010.10.023
Rytwinski, A., Crowe, K.A.: A simulation-optimization model for selecting the location of fuel-breaks to minimize expected losses from forest fires. Forest Ecol. Manag. 260(1), 1–11 (2010). doi:http://dx.doi.org/10.1016/j.foreco.2010.03.013
Zeng, Q., Yang, Z.: Integrating simulation and optimization to schedule loading operations in container terminals. Comput. Oper. Res. 36(6), 1935–1944 (2009). doi:http://dx.doi.org/10.1016/j.cor.2008.06.010
Zhen, L., Wang, K., Hu, H., Chang, D.: A simulation optimization framework for ambulance deployment and relocation problems. Comput. Ind. Eng. 72(0), 12–23 (2014). doi:http://dx.doi.org/10.1016/j.cie.2014.03.008
Acknowledgments
The project OTC Kaypal® MR is supported by Fond Unique Interministériel (FUI) and funded by BPI in France (www.bpifrance.fr). We like also to thank our research partners: 4S Network, DS Smith Packaging, FM Logistic, Association des transporteurs européens (ASTRE), Orange and GS1 France.
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Pan, S., Ballot, E. (2015). Open Tracing Container Repositioning Simulation Optimization: A Case Study of FMCG Supply Chain. In: Borangiu, T., Thomas, A., Trentesaux, D. (eds) Service Orientation in Holonic and Multi-agent Manufacturing. Studies in Computational Intelligence, vol 594. Springer, Cham. https://doi.org/10.1007/978-3-319-15159-5_26
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DOI: https://doi.org/10.1007/978-3-319-15159-5_26
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