Document Type: Original Article

Authors

1 Faculty of Management & Accounting, Department of Industrial Management, Faculty of Management & Accounting, Allameh Tabataba’i University, Tehran, Iran.

2 Faculty member, Department of Industrial Management, Faculty of Management & Accounting, Allameh Tabataba’i University, Tehran, Iran.

3 Department of Industrial Engineering, Islamic Azad University, Qazvin Branch, Qazvin, Iran.

Abstract

However, there is a lot of capital and plenty of manpower in the auto spare part industry, the enterprises and supply chains of this industry do not perform well in our country. This research models a three-level supply chain with multiple manufacturers, distribution centers and retailers, to minimize the total cost by taking into account various disruptions. The database of two active car spare parts companies for five strategic products in one year has been used. Then, the mathematical model is analyzed by considering disruptions based on three different sales policies: back orders, lost sales and outsourcing. Besides, to evaluate the performance of the model some numerical examples are used and analyzed to determine that algorithm works. Model solved efficiently by MATLAB software. The results show that the proposed algorithm of this research can neutralize the effect of the disruptions and cause a significant reduction in total cost of the system. The model is useful for helping decision makers to adopt an active approach to maintaining business benefits when disruptions take place in the supply chain.

Keywords

Aust, G., and Buscher, U., (2012). "Vertical cooperative advertising and pricing decisions in a manufacturer–retailer supply chain: A game theoretic approach", European Journal of Operational Research, pp. 473-482. 

Azad, N., Saharidis, G., Davoudpour, H., Maleky, H., and Yektamaram, S., (2013). "Strategies for protecting supply chain networks against facility and transportation disruptions : an improved Benders", Annals of Operations Research, Vol. 210, No. 1, pp. 125–163. 

Fakhrzad, M., and Alidoosti, Z., (2018). "A realistic perishability inventory management for location-inventory-routing problem based on Genetic Algorithm", Journal of Industrial Engineering and Management Studies, Vol. 5, No. 1, pp. 106-121. 

Giannakis, M., (2011). "Management of service supply chains with a service-oriented reference model: the case of management consulting", Supply Chain Management: An International Journal, Vol. 16, No. 5, pp. 346-361. 

Giri, B. C., and Sharma, S., (2014). "Manufacturer’s pricing strategy in a two-level supply chain with competing retailers and advertising cost dependent demand",  Economic Modelling, pp. 102-111.

isna. (2017). https://www.isna.ir/news/96022013352/. Tehran: isna.

Jimenez, M., Arenas, M., Bilbao, A., and Rodriguez, M. V., (2007). "Linear programming with fuzzy parameters: An interactive method resolution", Eur. J. Oper. Res., Vol. 177, pp. 1599–1609. 

Johari, M., Hosseini-Motlagh, S. M., and Nematollahi, M. R., (2016). "Coordinating pricing and periodic review replenishment decisions in a two-echelon supply chain using quantity discount contract", Journal of Industrial Engineering and Management Studies, Vol. 3, No. 2, pp. 58-87.

Kanchan, D., (2018). "Integrating lean systems in the design of a sustainable supply chain model", International Journal of Production Economics, pp. 177-190. 

Liang, G., and Renbin, X., (2017). "Outer synchronization and parameter identification approach to the resilient recovery of supply network with uncertainty", Physica A: Statistical Mechanics and its Applications, pp. 407-421. 

Maestrini, V., Luzzini, D., Maccarrone, P., and Caniato, F., (2017). "Supply chain performance measurement systems: A systematic review and research agenda", International Journal of Production Economics, pp. 299-315. 

Minkyun, K., and Sangmi, C., (2017). "The impact of supplier innovativeness, information sharing and strategic sourcing on improving supply chain agility: Global supply chain perspective", International Journal of Production Economics, pp. 42-52.

Paul, S. K., Sarker, R., and Essam, D., (2017). "A quantitative model for disruption mitigation in a supply chain", European Journal of Operational Research, pp. 881-895. 

Peng, p., snyder, L. V., Lim, A., and Liu, z., (2011). "Reliable logistics networks design with facility disruptions", Transportation Research Part B: Methodological, Vol. 45, No.8, pp. 1190–1211. 

Rezayi, A., (2012). Forecating product demand using backup vector regression (Case study: Irana tile). Dissertation for obtaining a Master's Degree; Semnan University. 

Shishebori, D., and Yousefi Babadi, A., (2015). "Dynamic supply chain network design for the supply of blood in disasters: A robust model with real world application", Transportation Research Part E: Logistics and Transportation Review, Vol. 70, pp. 225–244. 

Tamplin, M. L., (2017). Integrating predictive models and sensors to manage food stability in supply chains. Food Microbiology, In Press, Corrected Proof. 

Veronica , P. C., (2013). "A framework to facilitate interoperability in supply chains", International Journal of Computer Integrated Manufacturing, pp. 67-68. 

Zhi, C., Baofeng, H., Yuan, L., and Xiande, Z., (2015). "The impact of organizational culture on supply chain integration: a contingency and configuration approach", Supply Chain Management: An International Journal, pp. 24-41.