Iranian Journal of Trade Studies

Iranian Journal of Trade Studies

Resilient Supplier Selection and Order Allocation with Analysis of Interacting Risks in Bayesian Networks

Document Type : Research Paper

Authors
Mohammad Khosroabadi 1
Jafar Gheidar-Kheljani 2
Mohammad hosein Karimi Gavarashki 3
1 Department of Management & Industrial Engineering, Malek-Ashtar University of Technology, Tehran, Iran.
2 Associate Professor, Faculty of Industrial Engineering and Management, Malek Ashtar University of Technology, Tehran, Iran.
3 Faculty of Management and Industrial Engineering, Malek Ashtar University of Technology, Tehran, Iran.
10.22034/ijts.2024.2027866.3981
Abstract
Disruptions can impact not only suppliers and manufacturers but also influence each other at the beginning of the chain or customer demand at the end of the chain. In this paper, the extent of this impact is modeled and solved using a Bayesian network. Inflation rate is used to predict and reduce demand uncertainties in a linear programming model with two objective functions of increasing geographic dispersion and reducing total cost (transportation, purchasing, ordering, etc.). In this model, suppliers and manufacturers collaborate to increase supply chain resilience. For the first time, the concept of supplier resilience level is proposed. The proposed model for order allocation, in addition to price and other ordering costs, also considers the cost of improving the resilience level of suppliers. Also, customer satisfaction level is implicitly increased by increasing the cost of unmet demand. To this end, a case study was conducted in one of Iran’s automotive companies. To validate the proposed model, a numerical example was solved and sensitivity analysis was performed. To reduce the number of scenarios, fuzzy c-means clustering and balanced interaction analysis were used. The proposed model can prepare manufacturers for better decision-making and planning in the face of future risks and uncertainties.
Keywords
Resilient Supplier Selection / Lot Sizing / Scenario Reduction / Bayesian Network / Resilience Level / Supply Chain Risk Management

Subjects

 
Amer, M., Daim, T. U., & Jetter, A. (2013). A review of scenario planning. Futures, 46, 23-40. https://doi.org/10.1016/j.futures.2012.10.003
Tavana, A. B., Rabieh, M., Pishvaee, M. S., & Esmaeili, M. (2021). A Stochastic Mathematical Programming Approach to Resilient Supplier Selection and Order Allocation Problem: A Case Study in Iran Khodro Supply Chain. Scientia Iranica, 0(0), 0. https://doi.org/ 10.24200/sci.2021.56020.4515
Beiki, H., Seyedhosseini, S. M., Ponkratov, V. V., Zekiy, A. O., & Ivanov, S. A. (2021). Addressing a sustainable supplier selection and order allocation problem by an integrated approach: a case of automobile manufacturing. Journal of Industrial and Production Engineering, 38(4), 239-253. https://doi.org/10.1080/21681015.2021.1877202.
Bezdek, J., (1981). Pattern Recognition with Fuzzy Objective Function Algorithms, Plenum Press.
Chen, Z., Hammad, A. W., & Alyami, M. (2024). Building construction supply chain resilience under supply and demand uncertainties. Automation in Construction, 158, 105190. https://doi.org/10.1016/j.autcon.2023.105190.
Feng, J., & Gong, Z. (2020). Integrated linguistic entropy weight method and multi-objective programming model for supplier selection and order allocation in a circular economy: A case study. Journal of Cleaner Production, 277, 122597. https://doi.org/10.1016/j.jclepro.2020. 122597.
Hosseini, S., & Ivanov, D. (2019). A new resilience measure for supply networks with the ripple effect considerations: a Bayesian network approach. Annals of Operations Research, 319(1), 581-607. https://doi.org/10.1007/s10479-019-03350-8
Hosseini, S., & Ivanov, D. (2020). Bayesian networks for supply chain risk, resilience and ripple effect analysis: A literature review. Expert Systems with Applications, 161, 113649. https://doi.org/10.1016/j.eswa.2020.113649.
Hosseini, S., Morshedlou, N., Ivanov, D., Sarder, M.D., Barker, K., and Khaledf, A. A. (2019b). Resilient supplier selection and optimal order allocation under disruption risks. International Journal of Production Economics, 213, 124-137. https://doi.org/10.1016/j.ijpe.2019.03.018.
Kabgani, M., Shahbandarzadeh, H. (2019). Quantitative Analysis Criteria for Selecting
Suppliers in The Resilience Supply Chain Using Multi Criteria Decision Making
Techniques. Iranian Journal of Trade Studies, 23(90), 115-140. [In Persian]
Kaur, H., & Singh, S. P. (2021). Multi-stage hybrid model for supplier selection and order allocation considering disruption risks and disruptive technologies. International Journal of Production Economics, 231, 107830. https://doi.org/10.1016/j.ijpe.2020.107830
Kellner, F., & Utz, S. (2019). Sustainability in supplier selection and order allocation: Combining integer variables with Markowitz portfolio theory. Journal of Cleaner Production, 214, 462-474. https://doi.org/10.1016/j.jclepro.2018.12.315.
Kharidar, F., Pouya, A. (2016). The Taxonomy of supplier selection strategies and their
business performance (The case study of ceramic and tile companies). Iranian Journal
of Trade Studies, 20(80), 119-147. [In Persian]
Khoshfetrat, S., Galankashi, M. R., & Almasi, M. (2019). Sustainable supplier selection and order allocation: a fuzzy approach. Engineering Optimization, 52(9), 1494-1507. https://doi.org/10.1080/0305215x.2019.1663185.
Li, J., Wang, S., and Cheng, T.E. (2010). Competition and cooperation in a single-retailer two supplier supply chain with supply disruption. International Journal of Production Economics, 124(1), 137-150. https://doi.org/10.1016/j.ijpe.2009.10.017.
Liu, D., Li, Z., He, C., & Wang, S. (2021b). Risk-Averse Co-Decision for Lower-Carbon Product Family Configuration and Resilient Supplier Selection. Sustainability, 14(1), 384. https://doi.org/10.3390/su14010384.
Lu, Q., Jiang, Y., & Wang, Y. (2023). The effects of supply chain governance on supply chain resilience based on information processing theory. Industrial Management & Data Systems, 124(1), 291-318. https://doi.org/10.1108/imds-01-2023-0007
Mari, S. I., Memon, M. S., Ramzan, M. B., Qureshi, S. M., & Iqbal, M. W. (2019). Interactive Fuzzy Multi Criteria Decision Making Approach for Supplier Selection and Order Allocation in a Resilient Supply Chain. Mathematics, 7(2), 137. https://doi.org/10.3390/math7020137.
Modares, A., Farimani, N. M., & Dehghanian, F. (2024). A new vendor-managed inventory four-tier model based on reducing environmental impacts and optimal suppliers selection under uncertainty. Journal of Industrial and Management Optimization, 20(1), 188-220. https://doi.org/10.3934/jimo.2023074
Mohammed, A., Harris, I., Soroka, A., Naim, M., Ramjaun, T., & Yazdani, M. (2020). Gresilient supplier assessment and order allocation planning. Annals of Operations Research, 296(1-2), 335-362. https://doi.org/10.1007/s10479-020-03611-x
 Mohammed, A., Harris, I., & Govindan, K. (2019). A hybrid MCDM-FMOO approach for sustainable supplier selection and order allocation. International Journal of Production Economics, 217, 171-184. https://doi.org/10.1016/j.ijpe.2019.02.003
Nazari-Shirkouhi, S., Tavakoli, M., Govindan, K., & Mousakhani, S. (2023). A hybrid approach using Z-number DEA model and Artificial Neural Network for Resilient supplier Selection. Expert Systems With Applications, 222, 119746. https://doi.org/10.1016/j.eswa.2023.119746.
Parkouhi, S. V., Ghadikolaei, A. S., & Lajimi, H. F. (2019). Resilient supplier selection and segmentation in grey environment. Journal of Cleaner Production, 207, 1123-1137. https://doi.org/10.1016/j.jclepro.2018.10.007.
Rezaei, A., Aghsami, A., & Rabbani, M. (2021). Supplier selection and order allocation model with disruption and environmental risks in centralized supply chain. International Journal of Systems Assurance Engineering and Management, 12(6), 1036-1072. https://doi.org/10.1007/s13198-021-01164-1.
Rezaei, A., Rahiminezhad Galankashi, M., Mansoorzadeh, S., and Mokhatab Rafiei, F. (2020a) Supplier selection and order allocation with lean manufacturing criteria: an integrated MCDM and Bi-objective modelling approach. Engineering Management Journal, 32(4), 253-271. https://doi.org/10.1080/10429247.2020.1753490
Rezaei, A., Galankashi, M. R., Mansoorzadeh, S., & Rafiei, F. M. (2020b). Supplier Selection and Order Allocation with Lean Manufacturing Criteria: An Integrated MCDM and Bi-objective Modelling Approach. Engineering Management Journal, 32(4), 253-271. https://doi.org/10.1080/10429247.2020.1753490.
Torabi, S., Baghersad, M., & Mansouri, S. (2015). Resilient supplier selection and order allocation under operational and disruption risks. Transportation Research Part E Logistics and Transportation Review, 79, 22-48. https://doi.org/10.1016/j.tre.2015.03.005.
Taghavi, S. M., Ghezavati, V., Bidhandi, H. M., & Al-E-Hashem, S. M. J. M. (2022). Green-Resilient Supplier Selection and Order Allocation Under Disruption by Utilizing Conditional Value at Risk: Mixed Response Strategies. Process Integration and Optimization for Sustainability, 7(1-2), 359-380. https://doi.org/10.1007/s41660-022-00298-4.
Sabouhi, F., Pishvaee, M. S., & Jabalameli, M. S. (2018). Resilient supply chain design under operational and disruption risks considering quantity discount: A case study of pharmaceutical supply chain. Computers & Industrial Engineering, 126, 657-672. https://doi.org/10.1016/j.cie.2018.10.001.
Salehi, M., & Sayyah, M. (2017). Evaluation and Selection of Efficient Suppliers in terms
of Uncertainty -The Grey Data Envelopment Analysis Approach. Iranian Journal of
Trade Studies, 21(81), 181-203. [In Persian]
Shao, Y., Barnes, D., & Wu, C. (2022b). Sustainable supplier selection and order allocation for multinational enterprises considering supply disruption in COVID-19 era. Australian Journal of Management, 48(2), 284-322. https://doi.org/10.1177/03128962211066953.
Sohrabi, B., Tavassoli, S. H., & Jolai, F. (2021). The role of supply chain resilience in managing disruptions: A case study in the steel industry. International Journal of Production Research, 59(17), 5033-5050. https://doi.org/10.1007/s46551-044-00583-7.
Umar, M., Wilson, M. M. J., (2024). Inherent and adaptive resilience of logistics operations in food supply chains. Journal of Business Logistics, 45(1), e12362. https://doi.org/10.1111/jbl.12362.
 
 

  • Receive Date 01 May 2024
  • Revise Date 04 July 2024
  • Accept Date 23 July 2024