A Sustainability Comparison of Traditional Supply Chains and Physical Internet Supply Chains Using Simulation

Öz

Sustainability is one of the most important topics that should be considered by every sector because it helps to reduce the harmful environmental effects of operations. Supply chain operations have significant impacts on environmental, social and economic issues, and therefore, sustainable supply chains have become an important issue for the companies. Also, Physical Internet (PI) is one of the recent research topics in supply chain literature and it helps to provide sustainability. The contribution of this study to the literature is the comparison of traditional supply chain and Physical Internet supply chain structures with simulation in terms of sustainability. The simulation models are tested on realistic but hypothetical case studies. Each simulation model consists of three echelons (supplier, distribution center and retailer) and is developed by using ARENA 14.0 software. The physical internet and the traditional are compared according to carbon emissions, and the results are discussed in detail.

Anahtar Kelimeler

• Logistics,Physical Internet,Simulation,Supply Chain Management,Sustainability

Kaynakça

1. Carter, C.R. and Rogers, D.S., 2008. A framework of sustainable supply chain management: moving toward new theory. International journal of physical distribution & logistics management, 38(5), 360-387.
2. Fekpe, E. & Delaporte, Y. 2018. Sustainability integration and supply chain performance of manufacturing small and medium size enterprises. African Journal of Economic and Management Studies. 10(2), 130-147.
3. Montreuil, B., 2012. Physical Internet Manifesto, version 1.11. 1. CIRRELT Interuniversity Research Center on Enterprise Networks, Logistics and Transportation, 2-3.
4. Montreuil, B. 2011. Toward a Physical Internet: meeting the global logistics sustainability grand challenge. Logistics Research, 3(2-3), 71-87.
5. Meller, R. D., Montreuil, B., Thivierge, C. & Montreuil, Z. 2012. Functional Design of Physical Internet Facilities: A Road-Based Transit Center. Progress in Material Handling Research: 2012 (22).
6. Hakimi, D., Montreuil, B., Sarraj, R., Ballot, E., & Pan, S.Simulating a physical internet enabled mobility web: the case of mass distribution in France. In 9th International Conference on Modeling, Optimization & SIMulation-MOSIM'12, 2012, pp. 10-p.
7. Furtado, P., Fakhfakh, R., Frayret, J. M., & Biard, P. Simulation of a Physical Internet—Based transportation network. In Proceedings of 2013 International Conference on Industrial Engineering and Systems Management (IESM), 2013, pp. 1-8.
8. Sarraj, R., Ballot, E., Pan, S., Hakimi, D., & Montreuil, B. 2014. Interconnected logistic networks and protocols: simulation-based efficiency assessment. International Journal of Production Research, 52(11), 3185-3208.

9. Pan, S., & Ballot, E. 2015. Open tracing container repositioning simulation optimization: a case study of FMCG supply chain. In Service Orientation in Holonic and Multi-agent Manufacturing, 281-291.
10. Pan, S., Nigrelli, M., Ballot, E., Sarraj, R., & Yang, Y. 2015. Perspectives of inventory control models in the Physical Internet: A simulation study. Computers & Industrial Engineering, 84, 122-132.
11. Yang, Y., Pan, S., & Ballot, E. 2015. A model to take advantage of Physical Internet for vendor inventory management. IFAC-PapersOnLine, 48(3), 1990-1995.
12. Merkuryev, Y. A., Petuhova, J. J., Van Landeghem, R., & Vansteenkiste, S. Simulation-based analysis of the bullwhip effect under different information sharing strategies. In Proceedings 14th European Simulation Symposium. Germany, Dresden. 2002, pp. 294–299.
13. Prasoon, R., Agarwal, M., & Kumar, A. 2017. Replenishment Policy in a Two-Echelon Supply Chain: An Analysis Using Discrete-Event Simulation. International Journal of Business Analytics and Intelligence, 5(2), 37.
14. Cannella, S., Dominguez, R., Framinan, J. M., & Bruccoleri, M. 2018. Demand sharing inaccuracies in supply chains: A simulation study. Complexity.
15. Agarwal, A. 2018. Validation of Inventory models for Single-echelon Supply Chain using Discrete-event Simulation. arXiv preprint arXiv:1806.07427.
16. Banerjee, A., Burton, J., & Banerjee, S. 2003. A simulation study of lateral shipments in single supplier, multiple buyers supply chain networks. International Journal of Production Economics, 81, 103-114.
17. Tiacci, L., & Saetta, S. 2011. Reducing the mean supply delay of spare parts using lateral transshipments policies. International Journal of Production Economics, 133(1), 182-191.
18. Tlili, M., Moalla, M., & Campagne, J. P. 2012. The trans-shipment problem in a two-echelon, multi-location inventory system with lost sales. International Journal of Production Research, 50(13), 3547-3559.
19. Firouz, M., Keskin, B. B., & Melouk, S. H. 2017. An integrated supplier selection and inventory problem with multi-sourcing and lateral transshipments. Omega, 70, 77-93.
20. Yan, B., & Liu, L. 2018. Simulation of multi-echelon supply chain inventory transshipment models at different levels. Simulation, 94(7), 563-575.
21. Kellner, F., & Igl, J. 2015. Greenhouse gas reduction in transport: analyzing the carbon dioxide performance of different freight forwarder networks. Journal of Cleaner Production, 99, 177-191.