Designing a Closed Loop Supply Chain Network Considering the Supplier Disorder Risk and Production Time
Authors
Abstract
In the recent decades, raw materials and resources have been remarkable issues for researchers; in other words, they play an important role in manufacturing industries or service organizations. On the other hand, the population is increasing every day. An increase in the population means the increased demand for goods or services. Therefore, more resources are needed to deliver services or goods. For this reason, government agencies and environmental agencies have developed and enforced stringent laws against producers and service providers who have exceeded the permissible limits for the environment; in some cases, the use of resources has been even restricted. In the meantime, the supply chain has become one of the major issues that can greatly influence this issue. In this research, the supply chain of the closed loop has been modeled due to uncertainty, disturbances and cost of production. The purpose of this problem has been to minimize the cost of the system in question based on the location decisions, and flow rates between levels and sales. The Lagrangian liberation solution method is used to solve this NP-hard problem. In the end, a numerical example has been employed to test the model and the proposed solution method. The results show that the time of implementation of the large-scale problem with GAMS is higher than that of the proposed method.
Keywords
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15. Cui, T., Ouyang, Y., and Shen, Z. -J. M., “Reliable Facility Location Design under the Risk of Disruptions”, Operations Research, Vol. 58, No. 4, part-1, pp. 998-1011, 2010.
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19. Hatefi, S., and Jolai, F., “Robust and Reliable Forward-reverse Logistics Network Design under Demand Uncertainty and Facility Disruptions”, Applied Mathematical Modelling, Vol. 38, No. 9, pp. 2630-2647, 2014.
20. El-Sayed, M., Afia, N., and El-Kharbotly, A., “A Stochastic Model for Forward-reverse Logistics Network Design Under Risk”, Computers & Industrial Engineering, Vol. 58, No. 3, pp. 423-431, 2010.
21. Ramezani, M., Kimiagari, A. M., Karimi, B., and Hejazi, T. H.,“Closed-loop Supply Chain Network Design under a Fuzzy Environment”, Knowledge-Based Systems, Vol. 59, pp. 108-120, 2014.
22. Diabat, A., Battaïa, O., and Nazzal, D., “An Improved Lagrangian Relaxation-based Heuristic for a Joint Location-inventory Problem”, Computers & Operations Research, Vol. 61, pp. 170-178, 2015.
23. Kang, J. -H., and Kim, Y. -D., “Inventory Control in a Two-Level Supply Chain with Risk Pooling Effect”, International Journal of Production Economics, Vol. 135, pp. 116-124, 2012.
24. Badri, H., Bashiri, M., and Hejazi, T. H., “Integrated Strategic and Tactical Planning in a Supply Chain Network Design with a Heuristic Solution Method”, Computers & Operations Research, Vol. 40, pp. 1143-1154, 2013.
25. Fisher, M. L., “The Lagrangian Relaxation Method for Solving Integer Programming Problems”, Management Science, Vol. 50, pp. 1861-1871, 2004.
2. Li, J., Wang, S., and Cheng, T. E., “Competition and Cooperation in a Single-retailer Two-supplier Supply Chain with Supply Disruption”, International Journal of Production Economics, Vol. 124, No. 1, pp. 137-150, 2010.
3. Melo, M. T., Nickel, S., and Saldanha-da-Gama, F., “Facility Location and Supply Chain Management-A Review”, European Journal of Operational Research, Vol. 196. No. 2, pp. 401-412, 2009.
4. Fleischmann, M., Bloemhof-Ruwaard, J. M., Dekker, R., Van der Laan, E., Van Nunen, J. A., and Van Wassenhove, L. N., “Quantitative Models for Reverse Logistics: A Review”, European Journal of Operational Research, Vol. 103, No. 1, pp. 1-17, 1997.
5. Krikke, H., van Harten, A., and Schuur, P., “Business Case Oce: Reverse Logistic Network Re-design for Copiers”, OR-Spektrum, Vol. 21, No. 3, pp. 381-409, 1999.
6. Min, H., and Ko, H.-J., “The Dynamic Design of a Reverse Logistics Network From the Perspective of Third-party Logistics Service Providers”, International Journal of Production Economics, Vol. 113, No. 1, pp. 176-192, 2008.
7. Listeş, O., and Dekker, R., “A Stochastic Approach to a Case Study for Product Recovery Network Design”, European Journal of Operational Research, Vol. 160, No. 1, pp. 268-287, 2005.
8. Pishvaee, M. S., Farahani, R. Z., and Dullaert, W., “A Memetic Algorithm for Bi-objective Integrated Forward/reverse Logistics Network Design”, Computers & Operations Research, Vol. 37, No. 6, pp. 1100-1112, 2010.
9. Pishvaee, M., and Torabi, S., “A Possibilistic Programming Approach for Closed-loop Supply Chain Network Design under Uncertainty”, Fuzzy Sets and Systems, Vol. 161, No. 20, pp. 2668-2683, 2010.
10. Pishvaee, M. S., Rabbani, M., and Torabi, S. A., “A Robust Optimization Approach to Closed-loop Supply Chain Network Design under Uncertainty”, Applied Mathematical Modelling, Vol. 35, No. 2, pp. 637-649, 2011.
11. Ramezani, M., Bashiri, M., and Tavakkoli-Moghaddam, R., “A Robust Design for a Closed-loop Supply Chain Network under an Uncertain Environment”, The International Journal of Advanced Manufacturing Technology, Vol. 66, No. 5-8, pp. 825-843, 2013.
12. Hassanzadeh, Amin, S., and Zhang, G., “A Multi-objective Facility Location Model for Closed-loop Supply Chain Network under Uncertain Demand and Return”, Applied Mathematical Modelling, Vol. 37, No. 6, pp. 4165-4176, 2013.
13. Qi, L., Shen, Z. -J. M., and Snyder, L. V., “The Effect of Supply Disruptions on Supply Chain Design Decisions”, Transportation Science, Vol. 44, No. 2, pp. 274-289, 2010.
14. Aryanezhad, M. -B., Jalali, S. G., and Jabbarzadeh, A., “An Integrated Supply Chain Design Model with Random Disruptions Consideration”, African Journal of Business Management, Vol. 4, No. 12, pp. 2393-2401, 2010.
15. Cui, T., Ouyang, Y., and Shen, Z. -J. M., “Reliable Facility Location Design under the Risk of Disruptions”, Operations Research, Vol. 58, No. 4, part-1, pp. 998-1011, 2010.
16. Vahdani, B., Tavakkoli-Moghaddam, R., Modarres, M., and Baboli, A., “Reliable Design of a Forward/reverse Logistics Network under Uncertainty: A Robust-M/M/c Queuing Model”, Transportation Research Part E: Logistics and Transportation Review, Vol. 48, No. 6, pp. 1152-1168, 2012.
17. Vahdani, B., Tavakkoli-Moghaddam, R., Jolai, F., and Baboli, A., “Reliable Design of a Closed Loop Supply Chain Network under Uncertainty: An Interval Fuzzy Possibilistic Chance-constrained Model”, Engineering Optimization, Vol. 45, No. 6, pp. 745-765, 2013.
18. Azad, N., Saharidis, G. K., Davoudpour, H., Malekly, H., and Yektamaram, S. A., “Strategies for Protecting Supply Chain Networks Against Facility and Transportation Disruptions: An Improved Benders Decomposition Approach”, Annals of Operations Research, Vol. 210, No. 1, pp. 125-163, 2013.
19. Hatefi, S., and Jolai, F., “Robust and Reliable Forward-reverse Logistics Network Design under Demand Uncertainty and Facility Disruptions”, Applied Mathematical Modelling, Vol. 38, No. 9, pp. 2630-2647, 2014.
20. El-Sayed, M., Afia, N., and El-Kharbotly, A., “A Stochastic Model for Forward-reverse Logistics Network Design Under Risk”, Computers & Industrial Engineering, Vol. 58, No. 3, pp. 423-431, 2010.
21. Ramezani, M., Kimiagari, A. M., Karimi, B., and Hejazi, T. H.,“Closed-loop Supply Chain Network Design under a Fuzzy Environment”, Knowledge-Based Systems, Vol. 59, pp. 108-120, 2014.
22. Diabat, A., Battaïa, O., and Nazzal, D., “An Improved Lagrangian Relaxation-based Heuristic for a Joint Location-inventory Problem”, Computers & Operations Research, Vol. 61, pp. 170-178, 2015.
23. Kang, J. -H., and Kim, Y. -D., “Inventory Control in a Two-Level Supply Chain with Risk Pooling Effect”, International Journal of Production Economics, Vol. 135, pp. 116-124, 2012.
24. Badri, H., Bashiri, M., and Hejazi, T. H., “Integrated Strategic and Tactical Planning in a Supply Chain Network Design with a Heuristic Solution Method”, Computers & Operations Research, Vol. 40, pp. 1143-1154, 2013.
25. Fisher, M. L., “The Lagrangian Relaxation Method for Solving Integer Programming Problems”, Management Science, Vol. 50, pp. 1861-1871, 2004.
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