سامانه پشتیبانی خدمات اطلاعات

  اخبار و اعلانات

 آمار

تعداد نشریات163
تعداد شماره‌ها6,762
تعداد مقالات72,832
تعداد مشاهده مقاله131,723,120
تعداد دریافت فایل اصل مقاله103,475,634
Rahmani Meybodi, Farahnaz, Alem Tabriz, Akbar, Zandiyeh, Mostafa, Talebi, Davood. (1403). Designing a Resilient Three-level Intertwined Supply Network under Disruption and Uncertainty. , 16(4), 502-534. doi: 10.22059/imj.2024.381366.1008177
Farahnaz Rahmani Meybodi; Akbar Alem Tabriz; Mostafa Zandiyeh; Davood Talebi. "Designing a Resilient Three-level Intertwined Supply Network under Disruption and Uncertainty". , 16, 4, 1403, 502-534. doi: 10.22059/imj.2024.381366.1008177
Rahmani Meybodi, Farahnaz, Alem Tabriz, Akbar, Zandiyeh, Mostafa, Talebi, Davood. (1403). 'Designing a Resilient Three-level Intertwined Supply Network under Disruption and Uncertainty', , 16(4), pp. 502-534. doi: 10.22059/imj.2024.381366.1008177
Rahmani Meybodi, Farahnaz, Alem Tabriz, Akbar, Zandiyeh, Mostafa, Talebi, Davood. Designing a Resilient Three-level Intertwined Supply Network under Disruption and Uncertainty. , 1403; 16(4): 502-534. doi: 10.22059/imj.2024.381366.1008177

Designing a Resilient Three-level Intertwined Supply Network under Disruption and Uncertainty

Industrial Management Journal
دوره 16، شماره 4، 2024، صفحه 502-534    اصل مقاله (1.31 M)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22059/imj.2024.381366.1008177
نویسندگان
Farahnaz Rahmani Meybodi1؛ Akbar Alem Tabriz* 2؛ Mostafa Zandiyeh2؛ Davood Talebi3
1Ph.D. Candidate, Department of Industrial Management, Faculty of Industrial Management and Information Technology, Shahid Beheshti University, Tehran, Iran.
2Prof., Department of Industrial Management, Faculty of Industrial Management and Information Technology, Shahid Beheshti University, Tehran, Iran.
3Assistant Prof., Department of Industrial Management, Faculty of Industrial Management and Information Technology, Shahid Beheshti University, Tehran, Iran.
چکیده
Objective
The intertwined supply chain refers to a network of interconnected supply chains that, through long-term collaboration, can deliver products and services to multiple customers, even in the face of various disruptions. In the case of the tiles and ceramics industry, it is essential to enhance resilience and integration across all chains to address issues such as capacity limitations at centers, which are often due to the unavailability of raw materials and production machinery caused by sanctions. These challenges have led to inadequate production management and increased costs. The aim of this research is to design a resilient three-level intertwined supply network capable of withstanding disruptions and uncertainty while simultaneously increasing profit and enhancing resilience.
 
Methods
This research employs a capacity development strategy and supplier separation to address disruptions at centers and uses fuzzy chance-constrained programming to tackle demand uncertainty. The model of this research is a multi-product, multi-period, mixed-integer linear programming model. To solve the bi-objective optimization (profit and risk), the augmented epsilon constraint method was used, resulting in a Pareto solution set. To validate the model, real data related to the intertwined supply network of tiles and ceramics (interconnected supply chains of tiles and ceramics, glaze, and alumina balls) were used, and the model was solved using GAMS software.
 
Results
Based on the model output and the results of the decision variables, profit increased by three percent in the deterministic case compared to the uncertain case, while risk decreased by seven percent. The numerical results of the sensitivity analysis show that changing the epsilon parameter from zero to five-hundredths and from five-hundredths to one-tenth leads to a two to seven percent increase in profit. Additionally, the optimal capacity increase in the alumina ball production center is twenty percent, in the tile production center is ten percent, and in the glaze production center is thirty percent.
 
Conclusion
In the current global context, where the evolution of supply chains is moving towards intertwined supply networks, there are very few studies conducted on these networks. Given the nature of the intertwined supply network, the presented general model facilitates the transfer of raw materials or products through both intra-chain relationships (such as between suppliers and producers, and between producers and customers) and inter-chain relationships (such as between suppliers of one chain and those of another, between producers of one chain and those of another, between customers (production centers) of one chain and customers (final) of another, and the reverse relationship from producers of one chain to suppliers of another). The model simultaneously considers strategic decisions, including the selection of centers that require capacity increases, while optimizing operational decisions (such as production levels, inventory levels, and transportation levels) accordingly.
کلیدواژه‌ها
Fuzzy programming؛ Intertwined supply network؛ Mathematical modeling؛ Resilience؛ Uncertainty
مراجع
بهادران، مریم؛ فدایی اشکیکی، مهدی؛ طالقانی، محمد و همایون‌فر، مهدی (1401). طراحی شبکه زنجیره تأمین حلقه بسته تاب‌آور تحت شرایط ریسک‌های عملیاتی و اختلال با رویکرد مالوی. مدیریت صنعتی، 14(4)، 595- 617.

تقی‌زاده یزدی، محمدرضا؛ امراللهی بیوکی، ناهید و محمدی بالانی، عبدالکریم (1395). سنجش روابط میان عوامل تأثیرگذار بر پیاده‌سازی مدیریت زنجیرۀ تأمین سبز و رتبه‎بندی شرکت‎های حاضر در زنجیرۀ تأمین (مطالعۀ موردی: صنعت کاشی و سرامیک استان یزد). نشریه مدیریت صنعتی، 8(4)، 555- 574.

خلیلی، سید محمد؛ پویا، علیرضا؛ کاظمی، مصطفی و فکور ثقیه، امیرمحمد (1401). طراحی یک شبکه زنجیره تأمین بنزین پایدار و تاب‌آور تحت شرایط عدم قطعیت اختلال (مطالعه موردی: شبکه زنجیره تأمین بنزین استان خراسان رضوی). مدیریت صنعتی، 14(1)، 27- 79.

رحمانی میبدی، فرحناز؛ عالم تبریز، اکبر؛ زندیه، مصطفی و طالبی، داوود (1401). طراحی مدل شبکۀ تأمین درهم‌آمیخته با محوریت تاب‌آوری. نشریه پژوهش‌های مهندسی صنایع در سیستم‌های تولید، 10(20)، 77- 89.

شیشه‌بری، داوود؛ عبدالعظیمی، امید و عندلیب اردکانی، داوود (1400). زنجیرۀ تأمین حلقۀ بسته پایدار و تاب‌آور دارو با تأمین‌کنندۀ پشتیبان تحت شرایط بیماری کرونا (کووید 19). نشریه پژوهش‌های مهندسی صنایع در سیستم‌های تولید، 9(19)، 33-53.

صدیق‌پور، عبدالرضا (1398). مدل زنجیرۀ تأمین ارتجاعی در صنایع دارویی ایران. پایان‌نامه دکتری مدیریت صنعتی، تهران: دانشگاه شهید بهشتی.

موسوی، مهسا؛ جمالی، غلامرضا و قربانپور، احمد (1400). ارائه مدل بهینه‌سازی شبکه‎ زنجیره تأمین سبز ـ تاب‎آور در صنایع سیمان. مدیریت صنعتی، 13(2)، 222- 245.

 

References

Bahadoran, M., Fadaei Ashkiki, M., Taleghani, M. & Homayounfar, M. (2022). Designing a Resilient Closed-Loop Supply Chain Network under Operational Risk and Disruption Conditions by the Mulvey Approach, Industrial Management Journal, 14(4), 595-617.
(in Persian)

Bhat, S. & Aljuneidi, T. (2023). Viable Intertwined Supply Network: Modelling and Dynamic Analysis Using Artificial Neural Networks. Available at SSRN 4381244.

Bier, T., Lange, A. & Glock, C. H. (2020). Methods for mitigating disruptions in complex supply chain structures: a systematic literature review. International Journal of Production Research, 58(6), 1835-1856.

Chen, J., Sohal, A. S. & Prajogo, D. I. (2013). Supply chain operational risk mitigation: A collaborative approach. International Journal of Production Research, 51(7), 2186-2199.

Chibani, A., Delorme, X., Dolgui, A. & Pierreval, H. (2018). Dynamic optimisation for highly agile supply chains in e-procurement context. International journal of production research, 56(17), 5904-5929.

Cordeau, J. F., Klibi, W. & Nickel, S. (2021). Logistics network design. Network design with applications to transportation and logistics, 599-625.

Dehshiri, S. J. H. & Amiri, M. (2024). Considering the circular economy for designing closed-loop supply chain under hybrid uncertainty: A robust scenario-based possibilistic-stochastic programming. Expert Systems with Applications, 238, 121745.

Dehshiri, S. J. H., Amiri, M., Olfat, L. & Pishvaee, M. S. (2023). A robust fuzzy stochastic multi-objective model for stone paper closed-loop supply chain design considering the flexibility of soft constraints based on Me measure. Applied Soft Computing, 134, 109944.

Dubey, R., Gunasekaran, A. & Papadopoulos, T. (2019b). Disaster Relief Operations: Past, Present and Future. Annals of Operations Research, 283 (1-2), 1–8.

Echefaj, K., Charkaoui, A., Cherrafi, A. & Ivanov, D. (2024). Design of resilient and viable sourcing strategies in intertwined circular supply networks. Annals of Operations Research, 1-40.

Feizabadi, J., Gligor, D. M. & Choi, T. Y. (2023). Examining the resiliency of intertwined supply networks: A jury-rigging perspective. International Journal of Production Research, 61(8), 2432-2451.

Fraccascia, L., Giannoccaro, I. & Albino, V. (2017). Rethinking resilience in industrial symbiosis: conceptualization and measurements. Ecological Economics, 137, 148-162.

Ghanei, S., Contreras, I. & Cordeau, J. F. (2023). A two-stage stochastic collaborative intertwined supply network design problem under multiple disruptions. Transportation Research Part E: Logistics and Transportation Review, 170, 102944.

Golan, M. S., Jernegan, L. H. & Linkov, I. (2020). Trends and applications of resilience analytics in supply chain modeling: systematic literature review in the context of the COVID-19 pandemic. Environment Systems and Decisions, 40(2), 222-243.

Gorbaneva, O. & Ougolnitsky, G. (2022). Sustainability of Intertwined Supply Networks: A Game-Theoretic Approach. Games, 13(3), 35.

Hosseini, S., Ivanov, D. & Dolgui, A. (2019). Review of quantitative methods for supply chain resilience analysis. Transportation research part E: logistics and transportation review, 125, 285-307.

Ivanov, D. (2023). Collaborative emergency adaptation for ripple effect mitigation in intertwined supply networks. Annals of Operations Research, 1-17.

Ivanov, D. & Dolgui, A. (2019). Low-Certainty-Need (LCN) supply chains: a new perspective in managing disruption risks and resilience. International Journal of Production Research, 57(15-16), 5119-5136.

Ivanov, D. & Dolgui, A. (2020). Viability of intertwined supply networks: extending the supply chain resilience angles towards survivability. A position paper motivated by COVID-19 outbreak. International Journal of Production Research, 58(10), 2904-2915.

Ivanov, D., Dolgui, A. & Sokolov, B. (2019). The impact of digital technology and Industry 4.0 on the ripple effect and supply chain risk analytics. International Journal of Production Research, 57(3), 829-846.

Jabbarzadeh, A., Fahimnia, B., Sheu, J. B., & Moghadam, H. S. (2016). Designing a supply chain resilient to major disruptions and supply/demand interruptions. Transportation Research Part B: Methodological, 94, 121-149.

Khalili, S., M., Pooya, A., Kazemi, M., Fakoor Saghih, A., M., (2022). Designing a Sustainable and Resilient Gasoline Supply Chain Network under Uncertainty (Case study: Gasoline Supply Chain Network of Khorasan Razavi Province). Industrial Management Journal, 14(1), 27-79. (in Persian)

Mavrotas, G. (2009). Effective implementation of the ε-constraint method in multi-objective mathematical programming problems. Applied mathematics and computation, 213(2), 455-465.

Mousavi, M., Jamali, G. & Ghorbanpour, A. (2022). A Green-resilient Supply Chain Network Optimization Model in Cement Industries. Industrial Management Journal, 13(2), 222-245. (in Persian)

Rahmani Meybodi, F., Alem Tabriz, A., Zandiyeh, M. & Talabi, D. (2022). Designing a Model for Intertwined Supply Network Based on Resilience. Journal of Industrial Engineering Research in Production Systems, 10(20), 77-89. doi: 10.22084/ier.2023.27187.2108
(in Persian)

Ren, H., Wang, C., Mu, D., Lim, M. K., Yue, X., Hu, X., ... & Tsao, Y. C. (2024). Resilience strategies in an intertwined supply network: Mitigating the vulnerability under disruption ripple effects. International Journal of Production Economics, 109419.

Sedighpour, A. (2019). Resilient Supply Chain Model in Iran Pharmaceutical Industries. PHD Thesis Industrial Management, Shahid Beheshti University. (in Persian)

Shekarian, M. & Mellat Parast, M. (2021). An Integrative approach to supply chain disruption risk and resilience management: a literature review. International Journal of Logistics Research and Applications, 24(5), 427-455.

Shishebori, D., Abdolazimi, O., Andalib Ardakani, D., (2022). Sustainable and Resilient Closed-Loop Drug Supply Chain with Backup Suppliers under Coronavirus Disease Pandemic (COVID-19). Journal of Industrial Engineering Research in production systems, 9(19), 33-53. (in Persian)

Taghzadeh Yazdi, M. R., Amrollah Biuky, N. & Mohammadi Balani, A. (2017). Analyzing the Relationships between Green Supply Chain Management Implementation Factors and Ranking the Organizations in the Supply Chain (Case Study: Ceramic Tile Industry in Yazd Province). Industrial Management Journal, 8(4), 555-574. (in Persian)

Tsao, Y. C., Thanh, V. V., Lu, J. C. & Wei, H. H. (2021). A risk-sharing-based resilient renewable energy supply network model under the COVID-19 pandemic. Sustainable Production and Consumption, 25, 484-498.

Wang, J., Dou, R., Muddada, R.R. & Zhang, W. (2018). Management of a Holistic Supply Chain Network for Proactive Resilience: Theory and Case Study. Computers and Industrial Engineering 125: 668–677.

Wang, M. & Yao, J. (2023). Intertwined supply network design under facility and transportation disruption from the viability perspective. International Journal of Production Research, 61(8), 2513-2543.

Xu, J. & Zhou, X. (2013). Approximation based fuzzy multi-objective models with expected objectives and chance constraints: Application to earth-rock work allocation. Information Sciences, 238, 75-95.

آمار
تعداد مشاهده مقاله: 432
تعداد دریافت فایل اصل مقاله: 300





سامانه مدیریت نشریات علمی. قدرت گرفته از سیناوب