ارائه مدل ریاضی استوار برای طراحی بهینه شبکه زنجیره تأمین روبه‌جلو و عقب با استفاده از طراحی آزمایشات

فصلنامه مدیریت راهبردی در سیستم های صنعتی (مدیریت صنعتی سابق)

دوره 16، شماره 56، تیر 1400، صفحه 139-160   

نوع مقاله: مقاله پژوهشی

شناسه دیجیتال (DOI): 10.30495/imj.2021.684245

نویسندگان

حمید صفاری^* ؛ کریم آتشگر؛ مرتضی عباسی

دانشگاه صنعتی مالک اشتر

چکیده

توجه روزافزون به زنجیره تأمین‌های حلقه بسته و در نظرگیری جریان‌های رو به عقب در در این دسته از مدل های زنجیره تأمین، موجب ارائه مدل‌های ریاضی مختلفی در این حوزه شده است. این مقاله ابتدا مدلی استوار برای یک شبکه زنجیره تأمین با رویکرد جریان روبه‌جلو و عقب ارائه می نماید، و سپس با استفاده از روش طراحی آزمایشات میزان اثر هر یک از پارامترهای مدل‌سازی استوار و پارامترهای هزینه، نرخ تولید، و برگشت محصولات در زنجیره تأمین روبه‌جلو و عقب محصولات در حد بالا و پایین را تعیین می نماید. درنهایت این مقاله یک مدل جدید استوار بهینه شده را برای شبکه زنجیره تأمین حلقه بست ارائه می نماید. استفاده از طراحی آزمایشات و مدل‌سازی ریاضی استوار به‌صورت هم‌زمان که در این مقاله برای اولین بار انجام می شود، باعث شده است که: 1) سرعت رسیدن به جواب‌های بهینه افزایش پیدا کند ، 2) تصمیم‌گیرنده را در انتخاب مناسب پارامترهای مدل بصورت ساخت یافته یاری نماید. گزارش و نتایج ارائه شده، با توجه به اطلاعات صنعت آهن و فولاد کارا بودن استفاده از طراحی آزمایشات به‌منظور کاهش زمان حل مدل ریاضی و ارائه خطوط راهنما به تصمیم‌گیرنده در حوزه استراتژیک زنجیره تأمین را نشان می‌دهد.

کلیدواژه‌ها

طراحی شبکه زنجیره تأمین؛ طرحی آزمایشات؛ طراحی آزمایشات کسری؛ مدل‌سازی استوار

مراجع

1. Assarzadegan, P., & Rasti-Barzoki, M. (2016). Minimizing sum of the due date assignment costs, maximum tardiness and distribution costs in a supply chain scheduling problem. Applied Soft Computing, 47, 343-356.
2. Atashgar, K. (2019). Design Of Experiment And Taguchi Method (DOE). Malek Ashtar University of Technology. (in persian)
3. Bashiri, M., Badri, H., & Talebi, J. (2012). A new approach to tactical and strategic planning in production–distribution networks. Applied Mathematical Modelling, 36(4), 1703-1717.
4. Biehl, M., Prater, E., & Realff, M. J. (2007). Assessing performance and uncertainty in developing carpet reverse logistics systems. Computers & Operations Research, 34(2), 443-463.
5. Bozorgi-Amiri, A., Mahmoodian, V., Fahimnia, E., & Saffari, H. (2015). A new memetic algorithm for solving split delivery vehicle routing problem. Management Science Letters, 5(11), 1017-1022.
6. Blumberg, D., Zanjirani Farahani, R., Asgari, N.,  Hafezi, M.(2009). Revers Logestics. Institute for Trade studies and Research.
7. Cedillo-Campos, M., & Sánchez-Ramírez, C. (2013). Dynamic self-assessment of supply chains performance: an emerging market approach. Journal of applied research and technology, 11(3), 338-347.
8. Chompu-inwai, R., Jaimjit, B., & Premsuriyanunt, P. (2015). A combination of Material Flow Cost Accounting and design of experiments techniques in an SME: the case of a wood products manufacturing company in northern Thailand. Journal of Cleaner Production, 108, 1352-1364.
9. Fercoq, A., Lamouri, S., & Carbone, V. (2016). Lean/Green integration focused on waste reduction techniques. Journal of Cleaner production, 137, 567-578.
10. Fleischmann, M., Beullens, P., BLOEMHOF‐RUWAARD, J. M., & Van Wassenhove, L. N. (2001). The impact of product recovery on logistics network design. Production and operations management, 10(2), 156-173.
11. Gen, M., & Cheng, R. (1997). Genetic algorithms and engineering design. New York [ua].
12. Gholipoor, A., Paydar, M. M., & Safaei, A. S. (2019). A faucet closed-loop supply chain network design considering used faucet exchange plan. Journal of Cleaner Production, 235, 503-518.
13. Grobler, F., & Minnitt, R. C. A. (1999). The increasing role of direct reduced iron in global steelmaking.
14. http://www.steelonthenet.com
15. Jabbarzadeh, A., Haughton, M., & Khosrojerdi, A. (2018). Closed-loop supply chain network design under disruption risks: A robust approach with real world application. Computers & Industrial Engineering, 116, 178-191.
16. Jerbia, R., Boujelben, M. K., Sehli, M. A., & Jemai, Z. (2018). A stochastic closed-loop supply chain network design problem with multiple recovery options. Computers & Industrial Engineering, 118, 23-32.
17. Ko, H. J., & Evans, G. W. (2007). A genetic algorithm-based heuristic for the dynamic integrated forward/reverse logistics network for 3PLs. Computers & Operations Research, 34(2), 346-366.
18. Lee, D. H., & Dong, M. (2008). A heuristic approach to logistics network design for end-of-lease computer products recovery. Transportation Research Part E: Logistics and Transportation Review, 44(3), 455-474.
19. Sherafati, M., Bashiri, M., Tavakkoli-Moghaddam, R., & Pishvaee, M. S. (2019). Supply chain network design considering sustainable development paradigm: A case study in cable industry. Journal of Cleaner Production, 234, 366-380.
20. Mousavi, S. M., Pardalos, P. M., Niaki, S. T. A., Fügenschuh, A., & Fathi, M. (2019). Solving a continuous periodic review inventory-location allocation problem in vendor-buyer supply chain under uncertainty. Computers & Industrial Engineering, 128, 541-552.
21. Mulvey, J. M., Vanderbei, R. J., & Zenios, S. A. (1995). Robust optimization of large-scale systems. Operations research, 43(2), 264-281.
22. Özkır, V., & Başlıgil, H. (2013). Multi-objective optimization of closed-loop supply chains in uncertain environment. Journal of Cleaner Production, 41, 114-125.
23. Pishvaee, M. S., & Torabi, S. A. (2010). A possibilistic programming approach for closed-loop supply chain network design under uncertainty. Fuzzy sets and systems, 161(20), 2668-2683.
24. Pishvaee, M. S., Jolai, F., & Razmi, J. (2009). A stochastic optimization model for integrated forward/reverse logistics network design. Journal of Manufacturing Systems, 28(4), 107-114.
25. Pishvaee, M. S., Rabbani, M., & Torabi, S. A. (2011). A robust optimization approach to closed-loop supply chain network design under uncertainty. Applied Mathematical Modelling, 35(2), 637-649.
26. Ramezani, M., Bashiri, M., & Tavakkoli-Moghaddam, R. (2013). A new multi-objective stochastic model for a forward/reverse logistic network design with responsiveness and quality level. Applied Mathematical Modelling, 37(1-2), 328-344.
27. Ramezani, M., Bashiri, M., & Tavakkoli-Moghaddam, R. (2013). A robust design for a closed-loop supply chain network under an uncertain environment. The International Journal of Advanced Manufacturing Technology, 66(5-8), 825-843.
28. De Rosa, V., Gebhard, M., Hartmann, E., & Wollenweber, J. (2013). Robust sustainable bi-directional logistics network design under uncertainty. International Journal of Production Economics, 145(1), 184-198.
29. Saffari, H., Makui, A., Mahmoodian, V., & Pishvaee, M. S. (2015). Multi-objective robust optimization model for social responsible closed-loop supply chain solved by non-dominated sorting genetic algorithm. Journal of Industrial and Systems Engineering, 8(3), 42-58.
30. Salema, M. I. G., Póvoa, A. P. B., & Novais, A. Q. (2005). Design and planning of supply chains with reverse flows. In Computer Aided Chemical Engineering (Vol. 20, pp. 1075-1080.
31. Salema M. I. G., Póvoa A. P. B., Novais A. Q., (2007), An optimization model for the design of a capacitated multi-product reverse logistics network with uncertainty, European Journal of Operational Research,  179, 1063-1077.
32. Salema, M. I. G., Barbosa-Povoa, A. P., & Novais, A. Q. (2007). An optimization model for the design of a capacitated multi-product reverse logistics network with uncertainty. European journal of operational research, 179(3), 1063-1077.
33. Subramanian, P., Ramkumar, N., Narendran, T. T., & Ganesh, K. (2013). PRISM: PRIority based SiMulated annealing for a closed loop supply chain network design problem. Applied soft computing, 13(2), 1121-1135.
34. Sudarto, S., Takahashi, K., Morikawa, K., & Nagasawa, K. (2016). The impact of capacity planning on product lifecycle for performance on sustainability dimensions in Reverse Logistics Social Responsibility. Journal of Cleaner Production, 133, 28-42.
35. Narayana, S. A., Pati, R. K., & Padhi, S. S. (2019). Market dynamics and reverse logistics for sustainability in the Indian Pharmaceuticals industry. Journal of cleaner production, 208, 968-987.
36. Turrisi, M., Bruccoleri, M., & Cannella, S. (2013). Impact of reverse logistics on supply chain performance. International Journal of Physical Distribution & Logistics Management..
37. Vahdani, B., Tavakkoli-Moghaddam, R., Modarres, M., & Baboli, A. (2012). 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, 48(6), 1152-1168.
38. Olivares Vera, D. A., Olivares-Benitez, E., Puente Rivera, E., López-Campos, M., & Miranda, P. A. (2018). Combined use of mathematical optimization and design of experiments for the maximization of profit in a four-echelon supply chain. Complexity, 2018.
39. Wang, H. F., & Hsu, H. W. (2010). A closed-loop logistic model with a spanning-tree based genetic algorithm. Computers & operations research, 37(2), 376-389.
40. Yu, C. S., & Li, H. L. (2000). A robust optimization model for stochastic logistic problems. International journal of production economics, 64(1-3).