A novel model for a network of a closed-loop supply chain with recycling of returned perishable goods: A case study of dairy industry

Document Type: Research Paper

Authors

1 Department of Industrial Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran

2 ICT Research Institute, Iran Telecommunication Research Center, Tehran, Iran

Abstract

Recently, following the raise in expense pressures led to lower economic growth, an increasing number of manufacturers have begun to investigate eventuality of handling returned product in a more cost-effective and proper procedure. Significance of Reverse Logistics (RL) is becoming greater due to various governmental, societal, and environmental reasons. Number of papers present in the literature on RLs is a well index of its importance. In some industries, appropriately collected returned products could be used as raw material for another product, increasing Supply Chain (SC) profits and reducing the waste. Since, perishable goods have a limited shelf -life, they can be reusable if they are collected before they reach a critical time. Accordingly, in the present study, a Mixed Integer Linear Programming (MILP) model was introduced for a network of closed-loop SC with recycling of returned perishable goods, involving suppliers, producers, retailers, together with collection and disposal centers, in a multi-product, multi-period, and multi-level basis. To do this, a case study was performed on milk and yogurt products of a company in dairy industry. The model was solved and analyzed using GAMS software. Results obtained from assessment of the model indicated that, timely collection of perishable goods and their use in production of new products reduces total costs of perishable SC network.

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Main Subjects


Amin, S. H., & Zhang, G. (2012). A proposed mathematical model for closed-loop network configuration based on product life cycle. The International Journal of Advanced Manufacturing Technology, 58, 791–801.

Azadeh, A., Elahi, S., Farahani, M. H., & Nasirian, B. (2017) A genetic algorithm-Taguchi based approach to inventory routing problem of a single perishable product with transshipment. Computers & IndustrialEngineering, 104, 124–133.

Crama, Y., Rezaei Sadrabadi, M., Savelsbergh, M., & Van Woensel, T. (2018) Stochastic Inventory Routing for Perishable Products. Transportation Science.

Chung, H.M. Wee, Y. Po-Chung, (2008). Optimal policy for a closed-loop supply chain inventory system with remanufacturing. Mathematical and Computer Modelling, 6, 867–881.

Das, K., & Chowdhury, A. H. (2012). Designing a reverse logistics network for optimal collection, recovery and quality-based product-mix planning. International Journal of Production Economics, 135(1), 209-221.

De Giovanni, P. (2016). State-and control-dependent incentives in a closed-loop supply chain with dynamic returns. Dynamic Games and Applications, 6(1), 20-54.

Debo L, Toktay B, Van Wassenhove LN (2006). Joint life-cycle dynamics of new and remanufactured products. Production and Operations Management, 15(4), 498-513.

Demirel, H. Gökçen, (2008). A mixed integer programming model for remanufacturing in reverse logistics environment, The International Journal of Advanced Manufacturing Technology. 39(11-12), 1197–1206.

Deng, X., Yang, X., Zhang, Y., Li, Y., & Lu, Z. (2019). Risk propagation mechanisms and risk management strategies for a sustainable perishable products supply chain. Computers & Industrial Engineering, In Press.

Diabat, A., Abdallah, T., & Le, T. (2014). A hybrid tabu search based heuristic for the periodic distribution inventory problem with perishable goods. Annals of Operations Research, 242(2), 1–26.

Diop, N., Jaffee, S. M., & Aksoy, M. A., et al. (2005). Fruits and vegetables: global trade and competition in fresh and processed product markets. Global Agricultural Trade & Developing Countries, 237-257.

Du F, Evans GW, (2008). A bi-objective reverse logistics network analysis for post-sale service. Computers & Operations Research, 35(8), 2617–2634.

Eskandarpour, E. Masehian, R. Soltani, A. Khosrojerdi, (2014). A reverse logistics network for recovery systems and a robust meta heuristic solution approach. The International Journal of Advanced Manufacturing Technology, 74(9–12), 1393–406.

Francas D, Minner S (2009). Manufacturing network configuration in supply chains with product recovery. Omega, 37(4), 757-769.

Go, T.F., Wahab, D.A., Rahman, M.A., Ramli, R., Azhari, C.H. (2011). Disassemblability of endof- life vehicle: a critical review of evaluation methods. Journal of Cleaner Production, 19, 1536- 1546.

Hasanov, P., Jaber, M., & Tahirov, N. (2019). Four-level closed loop supply chain with remanufacturing. Applied Mathematical Modelling, 66, 141-155.

Heydari, J., Govindan, K., & Sadeghi, R. (2018). Reverse supply chain coordination under stochastic remanufacturing capacity. International Journal of Production Economics, 202, 1-11.

Jia J. & Hu Q. (2011). Dynamic ordering and pricing for a perishable goods supply chain. Computers & Industrial Engineering, 60(2),302-309.

Junior, M. L., Filho, M. G. (2012). Production planning and control for remanufacturing: literature review and analysis. Production Planning & Control, 23(6), 419-435.

Kim, K., Song, I., Kim, J., & Jeong, B. (2006). Supply planning model for remanufacturing system in reverse logistics environment. Computers & Industrial Engineering, 51(2), 279-287.

Kim, T., Glock, C. H., & Kwon, Y. (2014). A closed-loop supply chain for deteriorating products under stochastic container return times. Omega, 43(2), 30–40.

Krikke, H., Bloemhof-Ruwaard, J., Van Wassenhove, L. N. (2003). Concurrent product and closed-loop supply chain design with an application to refrigerators. International journal of production research, 41(16), 3689-3719.

Kurdve, M., Shahbazi, S., Wendin, M., Bengtsson, C., Wiktorsson, M. (2015). Waste flow mapping to improve sustainability of waste management: a case study approach. Journal of Cleaner Production, 98, 304-315.

Lee JE, Gen M, Rhee KG (2009) Network model and optimization of reverse logistics by hybrid genetic algorithm. Computers & Industrial Engineering, 56(3), 951-964.

Liao, T.-Y. (2018). Reverse logistics network design for product recovery and remanufacturing. Applied Mathematical Modelling, 60, 145-163.

Li X, Olorunniwo F (2008). An exploration of reverse logistics practices in three companies. Supply Chain Management: An International Journal, 13(5), 381-386.

Liu K.F & Liu X. (2013). A stochastic model for perishable products production and distribution with operation risks. Industrial Engineering Journal, 16(1), 38-44.

Mutha, A., Pokharel, S. (2009). Strategic network design for reverse logistics and remanufacturing using new and old product modules. Computers & Industrial Engineering, 56, 334-346.

Nakandala, D., Lau, H., & Zhang, J. (2016) Cost-optimization modelling for fresh food quality and transportation. Industrial Management & Data Systems, 116(3), 564–583.

Noya I., Aldea X., & Gasol C. M., et al.(2016) .Carbon and water footprint of pork supply chain in Catalonia: From feed to final products. Journal of Environmental Management, 171,133-143.

Pati RK, Vrat P, Kumar P, (2008). A goal programming model for paper recycling system. Omega, 36(3), 405–417

Petek J, Glavic P (1996). An integral approach to waste minimization in process industries. Resources, Conservation and Recycling, 17(3), 169-188.

Shi J, Zhang G, Sha J, Amin SH, (2010). Coordinating production and recycling decisions with stochastic demand and return. Journal of Systems Science and Systems Engineering. 19(4), 385–407.

Radzi R.M., Saidon IM., Ghani NA., (2016). Risk Management in Food Supply Chains by Japanese Food Companies in Malaysia. International Journal of Business Management and Economic Research, 7(6), 778-787.

Rijpkema, W. A., Rossi, R., & Jack, G.A.J. van der Vorst. (2014). Effective sourcing strategies for perishable products supply chains. International Journal of Physical Distribution & Logistics Management, 44(6), 494–510.

Rogers DS, Tibben-Lembke R (2001). An examination of reverse logistics practices. Journal of Business Logistics, 22(2), 129-148.

Rowshannahad, M., Absi, N., Dauzère-Pérès, S., & Cassini, B. (2018). Multi-item bi-level supply chain planning with multiple remanufacturing of reusable by-products. International Journal of Production Economics, 198, 25-37.

Sasikumar, P., Kannan, G. (2009). Issues in reverse supply chain, part III: classification and simple analysis. International Journal of Sustainable Engineering, 2(1), 2-27.

Scalia, G. L., Micale, R., Miglietta, P. P., & Toma, P. (2019). Reducing waste and ecological impacts through a sustainable and efficient management of perishable food based on the Monte Carlo simulation. Ecological Indicators, 97, 363-371.

Song, Q., Li, J., Zeng, X. (2015). Minimizing the increasing solid waste through zero waste  strategy. Journal of Cleaner Production, 104, 199-210.

Tahirov, N., Hasanov, P., & Jaber, M. Y. (2016). Optimization of closed-loop supply chain of multi-items with returned subassemblies. International Journal of Production Economics, 174, 1-10.

Taleizadeh, A. A., Haghighi, F., & Niaki, S. T. (2019). Modeling and solving a sustainable closed loop supply chain problem with pricing decisions and discounts on returned products. Journal of Cleaner Production, 207, 163-181.

Toma, P., Massari, S., Miglietta, P.P(2016). Natural resource use efficiency and economic productivity. In: Massari, S., Sonnemann, G., Balkau, F. (Eds.), Life Cycle Approaches to Sustainable Regional Development, pp. 143–148.

Vahdani, B., Niaki, S. T. A., & Aslanzade, S. (2017) Production-inventory-routing coordination with capacity and time window constraints for perishable products: Heuristic and meta-heuristic algorithms. Journal of Cleaner Production, 161, 598–618.

Zhang, K., & Feng, S. (2014). Research on revenue sharing coordination contract in automobile closed-loop supply chain. In Service Operations and Logistics, and Informatics (SOLI), 2014 IEEE International Conference on (pp. 298-302). IEEE.