Integrated optimization of facility location, inventory control, fleet and routing in the supply chain of perishable products using an optimization approach based on hybrid simulation
الموضوعات :
مهدی سوهانیان
1
,
رضا احتشام راثی
2
,
رضا رادفر
3
1 - PHD Student
2 - گروه مدیریت صنعتی، واحد قزوین، دانشگاه آزاد اسلامی، قزوین، ایران
3 - Department of Industrial Management, Faculty of Industrial Management, Islamic Azad University, Science and Research Unit, Tehran, Iran
الکلمات المفتاحية: supply chain, perishable, factor-based modeling, discrete event simulation, optimization, meta-heuristic,
ملخص المقالة :
The supply chain of perishable products has high complexity due to the short lifespan of the products. For this reason, it is necessary to evaluate various issues in the supply chain such as location, inventory and logistics in an integrated manner by using flexible tools. The purpose of this research is to present an optimization approach based on event-factor-based discrete hybrid simulation for the integrated optimization of facility location, inventory control, fleet composition and routing in the supply chain of perishable products.The optimization process is performed using meta-heuristic algorithms. In order to conduct a case study, the supply chain of one of the largest producers of dairy products in the country has been considered, and due to the high demand and production of ice cream, this product has been considered as a perishable product of the supply chain. The results show that the integrated optimization of the research topic leads to a significant improvement in product waste, reducing the time of processing and delivering orders, and reducing the number of fleets.
1. Abbas, H., Zhao, L., Gong, X., Jiang, M., & Faiz, N. (2022). Environmental effects on perishable product quality and trading under OBOR supply chain different route scenarios. Environmental Science and Pollution Research, 29(45), 68016-68034
. 2. Ahumada, O., and Villalobos, J.R. (2011b). "Operational model for planning the harvest and distribution of perishable agricultural products", International Journal of Production Economics, 133(2), 677–687
. 3. Biuki, M., Kazemi, A., & Alinezhad, A. (2020). An integrated location-routing-inventory model for sustainable design of a perishable products supply chain network. Journal of Cleaner Production, 260, 120842
. 4. Chao, C., Zhihui, T., & Baozhen, Y. (2019). Optimization of two-stage location–routing–inventory problem with time-windows in food distribution network. Annals of Operations Research, 273, 111-134
. 5. Gosavi, A. (2015). Simulation-based optimization (pp. 47-55). Berlin: Springer
. 6. Golestani, M., Moosavirad, S. H., Asadi, Y., & Biglari, S. (2021). A multi-objective green hub location problem with multi item-multi temperature joint distribution for perishable products in cold supply chain. Sustainable Production and Consumption, 27, 1183-1194
. 7. Fahmy, S. A., Zaki, A. M., & Gaber, Y. H. (2023). Optimal locations and flow allocations for aggregation hubs in supply chain networks of perishable products. Socio-Economic Planning Sciences, 86, 101500
. 8. Ferguson, M.E., Ketzenberg, M.E., 2005. Information Sharing to Improve Retail Product Freshness of Perishables. Prod. Oper. Manage. 15 (1), 57–73
. 9. Jouzdani, J., & Govindan, K. (2021). On the sustainable perishable food supply chain network design: A dairy products case to achieve sustainable development goals. Journal of Cleaner Production, 278, 123060
. 10. Kleijnen, J. P. C., & Wan, J. (2007). Optimization of simulated systems: OptQuest and alternatives. Simulation Modelling Practice and Theory, 15(3), 354–362
. 11. Kuo, M. S. (2011). Optimal location selection for an international distribution center by using a new hybrid method. Expert Systems with Applications, 38(6), 7208-7221
. 12. Lacomme, P., Moukrim, A., Quilliot, A., & Vinot, M. (2018). Supply chain optimisation with both production and transportation integration: multiple vehicles for a single perishable product. International Journal of Production Research, 56(12), 4313-4336
. 13. Liu, A., Zhu, Q., Xu, L., Lu, Q., & Fan, Y. (2021). Sustainable supply chain management for perishable products in emerging markets: An integrated location-inventory-routing model. Transportation Research Part E: Logistics and Transportation Review, 150, 102319
. 14. Macal, C. M. (2010, December). To agent-based simulation from system dynamics. In Proceedings of the 2010 winter simulation conference (pp. 371-382). IEEE
. 15. Macal, C., & North, M. (2014, December). Introductory tutorial: Agent-based modeling and simulation. In Proceedings of the winter simulation conference 2014 (pp. 6-20). IEEE
. 16. Martin, R., 2015. China must Improve its Cool Supply Chain to Keep Pace with Demand for Fresh Food. URL: http://theloadstar.co.uk/coolstar/china-mustimproveits-cool-supply-chain-to-keep-pace-with-demand-for-fresh-food
/. 17. Mihajlović, J., Rajković, P., Petrović, G., & Ćirić, D. (2019). The selection of the logistics distribution center location based on MCDM methodology in southern and eastern region in Serbia. Operational Research in Engineering Sciences: Theory and Applications, 2(2), 72-85
. 18. Mirabelli, G., & Solina, V. (2022). Optimization strategies for the integrated management of perishable supply chains: A literature review. Journal of Industrial Engineering and Management (JIEM), 15(1), 58-9
19. Moreira, F. S., Jans, R., Guimarães, L., Cordeau, J. F., & Almada-Lobo, B. (2019). Solving a large multi-product production-Routing problem with delivery time windows
. 20. Onggo, B. S., Panadero, J., Corlu, C. G., & Juan, A. A. (2019). Agri-food supply chains with stochastic demands: A multi-period inventory routing problem with perishable products. Simulation Modelling Practice and Theory, 97, 101970
. 21. Partovi, F., Seifbarghy, M., & Esmaeili, M. (2023). Revised solution technique for a bi-level location-inventory-routing problem under uncertainty of demand and perishability of products. Applied Soft Computing, 133, 109899
. 22. Pitt, J.I., Hocking, A.D., 2009. Fungi and Food Spoilage. Springer
. 23. Qiu, Y., Qiao, J., & Pardalos, P. M. (2019). Optimal production, replenishment, delivery, routing and inventory management policies for products with perishable inventory. Omega, 82, 193-204
. 24. Song, L., & Wu, Z. (2023). An integrated approach for optimizing location-inventory and location-inventory-routing problem for perishable products. International Journal of Transportation Science and Technology, 12(1), 148-172
. 25. Soysal, M., Bloemhof-Ruwaard, J. M., Haijema, R., & van der Vorst, J. G. (2018). Modeling a green inventory routing problem for perishable products with horizontal collaboration. Computers & Operations Research, 89, 168-182
. 26. Sun, H., Sun, S., Zhou, Y., & Xue, Y. (2023). Trade-offs between economic and environmental goals of production-inventory-routing problem for multiple perishable products. Computers & Industrial Engineering, 178, 109133
. 27. Suryawanshi, P., & Dutta, P. (2021). Distribution planning problem of a supply chain of perishable products under disruptions and demand stochasticity. International Journal of Productivity and Performance Management
. 28. Violi, A., Laganá, D., & Paradiso, R. (2020). The inventory routing problem under uncertainty with perishable products: an application in the agri-food supply chain. Soft computing, 24(18), 13725-13740
.
