پیوندهای مفید
آمار
| تعداد نشریات | 21 |
| تعداد شماره‌ها | 628 |
| تعداد مقالات | 9,179 |
| تعداد مشاهده مقاله | 67,527,010 |
| تعداد دریافت فایل اصل مقاله | 8,061,755 |
ارائه مدل بهینه‌سازی ریاضی برای زنجیره تأمین چند محصولی با امکان وقوع اختلال در تأمین‌کننده در شرایط تحریم (مطالعه موردی صنایع تعمیراتی پالایشگاهی) | ||
| مدل سازی در مهندسی | ||
| مقاله 8، دوره 18، شماره 60، خرداد 1399، صفحه 107-125 اصل مقاله (1.91 M) | ||
| نوع مقاله: مقاله صنایع | ||
| شناسه دیجیتال (DOI): 10.22075/jme.2020.19137.1807 | ||
| نویسندگان | ||
| امیر رحیمی منش1؛ حمزه امین طهماسبی* 2؛ کامبیز شاهرودی3 | ||
| 1دانشجوی دکتری مدیریت صنعتی، دانشکده مدیریت و حسابداری، دانشگاه آزاد اسلامی، واحد رشت، رشت، ایران. | ||
| 2استادیار گروه مهندسی صنایع، دانشکده فنی و مهندسی شرق، دانشگاه گیلان | ||
| 3استادیار،دانشکده مدیریت و حسابداری،دانشگاه آزاد اسلامی، واحد رشت، رشت، ایران. | ||
| تاریخ دریافت: 06 آذر 1398، تاریخ بازنگری: 06 بهمن 1398، تاریخ پذیرش: 16 بهمن 1398 | ||
| چکیده | ||
| در این پژوهش مدل بهینه‌سازی شده ریاضی برای زنجیره تأمین چند محصولی با امکان وجود اختلال در تأمین‌کننده در شرایط تحریم، ارائه شده است. یک زنجیره تأمین شامل هم‌راستایی و همسویی شرکت‌هایی است که محصولات یا خدمات را به بازار عرضه می‌کنند. در راستای مدیریت زنجیره تأمین چند محصولی، نیاز به تأمین اقلام و مواد اولیه جهت استفاده در فرآیندها وجود دارد و تأمین این اقلام با عدم قطعیت مواجه است به‌گونه‌ای که ممکن است تأمینکنندگان، بخشی از تقاضای سفارش داده‌شده را در زمان موردنیاز در اختیار سفارشدهنده قرار ندهند. به‌منظور مقابله با این شکل از عدم قطعیت، دو نوع تأمین‌کننده موردنظر است. دسته اول تأمین‌کننده های ارزان‌قیمت ولی غیرمطمئن است و در مقابل، دسته دوم تأمین‌کننده‌ها وجود دارند که مطمئن هستند ولی گران‌تر از دسته اول میباشند. اقلام دریافتی از تأمین‌کننده ها، در فرآیند تولید یا تعمیرات مورد استفاده قرار می‌گیرد و مدلی مدون برای مدیریت این فرآیند میبایست ارائه گردد. جهت ادغام این تصمیمات در قالب مدل یکپارچه، مدل تصمیم گیری دومرحله‌ای تصادفی بکار رفته است و در حل مسئله پیشنهادی از روش تقریب میانگین نمونه گیری استفاده شده است. نتایج نشانمیدهد که با استفاده از مدل دومرحله‌ای تصادفی به‌اندازه 84/6 درصد در خروجی های مسئله بهبود ایجاد می‌شود و همین‌طور استفاده از تأمین‌کننده گران در کنار تأمین‌کننده ارزان منجر به بهبود خروجی‌های مدل به‌اندازه 9/14 درصد گردید. | ||
| کلیدواژه‌ها | ||
| زنجیره تأمین؛ بهینه‌سازی ریاضی؛ اختلال؛ مدل دو مرحله تصادفی؛ تقریب میانگین نمونهگیری | ||
| عنوان مقاله [English] | ||
| Providing a mathematical optimization model for the multi-product supply chain despite the possibility of supplier disruption under sanctions (Case Study of Refinery Repair Industries) | ||
| نویسندگان [English] | ||
| Amir Rahimimanesh1؛ Hamzeh Amin-Tahmasbi2؛ Kambiz shahroodi3 | ||
| 1PhD student in Industrial Management, Department of Management and Accounting, Rasht Branch, Islamic Azad University, Rasht, Iran. | ||
| 2Assistant Prof. Department of Industrial Engineering, Faculty of Technology and Engineering, East of Guilan, University of Guilan, Iran | ||
| 3Assistant Professor, Department of Management and Accounting, RashtBranch, Islamic Azad University, Rasht, Iran. | ||
| چکیده [English] | ||
| In this study, an optimized mathematical model for a multi-product supply chain with the possibility of supplier disruption under sanctions is presented. A supply chain involves the alignment of companies that market products or services. In order to manage the multi-product supply chain, there is a need for supplies and raw materials to be used in the processes and the supply of these items is subject to uncertainty so that suppliers may meet part of the ordered demand at the required time. Not to be provided to the customer. There are two types of suppliers to deal with this form of uncertainty. The first category is low-cost but unreliable suppliers, and in the second, there are suppliers that are reliable but more expensive than the first. Items received from suppliers are used in the manufacturing or repair process and a model for managing this process must be provided. To integrate these decisions into an integrated model, a stochastic two-stage decision model has been used and the approximation of mean sampling method has been used to solve the proposed problem. The results show that using the random two-step model results in an improvement of 6.84% in the outputs of the problem and also the use of suppliers along with the cheap supplier leads to the improvement of the model outputs. It was 14.9%. | ||
| کلیدواژه‌ها [English] | ||
| Supply Chain, Mathematical Optimization, Disturbance, Two-Stage Stochastic Model, Mean Sampling Approx | ||
| مراجع | ||
|
]1[علی‌اکبر حسنی، "طراحی زنجیرهتأمین رقابتی تحت شرایط تحریم با در نظرگرفتن استراتژی‌های بازگشت‌پذیر: نمونهموردی صنایع تجهیزات پزشکی ایران"، کنفرانس بین‌المللی اقتصاد در شرایط تحریم، بابلسر، ایران، 31 شهریور، دوره 3، 1394. [2] J.P. Ribeiro and A. Barbosa-Povoa, "Supply Chain Resilience: Definitions and Quantitative Modelling Approaches– A Literature Review ", Computers & Industrial Engineering, Vol. 115, No. 1, January 2018, pp. 109-122. [3] M. Abdel-Basset, M. Gunasekaran, M. Mohamed and N.Chilamkurti, "A framework for risk assessment, management and evaluation: Economic tool for quantifying risks in supply chain", Future Generation Computer Systems, Vol. 90, No. 1, January 2019, pp. 489-502. [4] A. Azadegan, R. Srinivasan, C. Blome and K. Tajeddini, "Learning from near-miss events: An organizational learning perspective on supply chain disruption response", International Journal of Production Economics, Vol. 216, No. 11, October 2019, pp. 215-226. [5] W. Yu, M. A. Jacobs, R. Chavez and J. Yang "Dynamism, disruption orientation, and resilience in the supply chain and the impacts on financial performance: A dynamic capabilities perspective", International Journal of Production Economics, Vol. 218, No. 24, December 2019, pp. 352-362. [6] N. Goldbeck, P. Angeloudis, and W. Ochieng, "Optimal supply chain resilience with consideration of failure propagation and repair logistics", Transportation Research Part E: Logistics and Transportation Review, Vol. 133, No. 2, January 2020, 101830. [7] M. Yuan, H. Zhang, B. Wang, L. Huang, K. Fang and Y. Liang, "Downstream oil supply security in China: Policy implications from quantifying the impact of oil import disruption", Energy Policy, Vol. 136, No. 4, January 2020, 111077. ]8[ وحید نعمتی ابوذر و محمدعلی بهشتینیا، "ترکیب روش‌های فرآیند تحلیل سلسلهمراتبی فازی و تاپسیس فازی برای انتخاب تأمینکنندگان (مطالعهموردی: شرکت تبلیغاتی)"، نشریه مدل‌سازی در مهندسی، دوره 15، شماره 48، بهار 1396، صفحه 68-84. ]9[ ساموئل یوسفی و مصطفی جهانگشای رضایی، "ارائه مدل ترکیبی برای انتخاب تأمینکنندگان کارا در محیط رقابتی و تحت عدم قطعیت تقاضا"، نشریه مدل‌سازی در مهندسی، دوره 15، شماره 51، زمستان 1396، صفحه 299-317. [10] C.S.Tang, "Perspectives in supply chain risk management", International Journal of Production Economics, [11] M. Christopher and H.Lee, "Mitigating supply chain risk through improved confidence", International Journal of Physical Distribution & Logistics Management,Vol. 34, No. 5, June 2004, pp. 388-396. [12] C.S.Tang, "Robust strategies for mitigating supply chain disruptions", International Journal of Logistic:Research and Applications, Vol. 9, No. 1, January 2007, pp. 33-45.
[13] J. B.Rice, F.Caniato, and J.Fleck, "Supply chain response to terrorism Creating resilient and secure supply chains", Report by MIT Center for Transportation and Logistics, April 2003. [14] Y.Sheffi and J.Rice, "A supply chain view of the resilient enterprise", MIT Sloan management review, October 2005. [15] H. L.Lee and S.Whang, "Higher supply chain security with lower cost: Lessons from total quality management", International Journal of Production Economics, Vol. 96, No. 3, June 2005, pp. 289-300. [16] Y.Sheffi, "Supply chain management under the threat of international terrorism", International Journal of Logistics Management, Vol. 12, No. 2, July 2001, pp.1-11. [17] G. Li, Y. Lin, S.Wang, and H. Yan, "Enhancing agility by timely sharing of supply information", Supply Chain Management: An International Journal, Vol. 11, No. 5, September 2006, pp.425-435. [18] M. Parlar and D. Berkin, "Future supply uncertainty in EOQ models", Naval Research Logistics (NRL),Vol. 38, No. 1, February 1991, pp. 107-121. [19] F.Zeynep Sargut and L. Qi," Analysis of a two-party supply chain with random disruptions", Operations Research Letters, Vol. 40, No. 2, March 2012, pp. 114-122. [20] T. Xiao and L. Qi, "Price competition, cost and demand disruptions and coordination of a supply chain with one manufacturer and two competing retailer",Omega,Vol. 36, No. 5, October 2008, pp. 741-753. [21] B.Keren, "The single-period inventory problem: Extension to random yield from the perspective of the supply chain", Omega, Vol. 37, No. 4, August 2009, pp. 801-810. ]22 [زهرا بهرامی، سید حمیدرضا پسندیده و محمد محمدی، "مدل‌سازی و حل یک سیستم مدیریت موجودی توسط فروشنده چندکالایی با محدودیت‌های تصادفی گنجایش انبار و بودجه"، نشریه مطالعات مدیریت صنعتی، دوره 16، شماره 51، زمستان 1397، صفحه 1-27. [23] D.Simchi-Levi, H. Wang, and Y. Wei, "Increasing supply chain robustness through process flexibility and inventory", Production And Operations Management, Vol. 27, No. 8, August 2018, pp. 1476-1491. [24] Dp. Song, Jx. Dong and J. Xu, "Integrated inventory management and supplier base reduction in a supply chain with multiple uncertainties", European Journal of operational research, Vol. 232, No. 3, February 2014, pp. 522-536. [25] F. Firouzi, E. Baglieri and M. Jaber, "Two-product inventory management with fixed costs and supply uncertainty", Applied Mathematical Modelling, Vol. 38 ,No .23, December 2014, pp. 5635-5650. [26] T. Sawik, "Two-period vs. multi-period model for supply chain disruption management", International Journal of Production Research, Vol. 57, No. 14, August 2018, pp. 4502-4518. [27] S. K. Paul, R. Sarker and D. Essam, "Managing disruption in an imperfect production–inventory system", Computers & Industrial Engineering, Vol. 84, No. 3, June 2015, pp. 101-112. [28] S. K. Paul, R. Sarker and D. Essam,"managing risk and disruption in production-inventory and supply chain systems: a review", Journal of Industrial & Management Optimization, Vol. 12, No. 3, July 2015, pp. 1009-1029. [29] M. Yao and S. Minner, "Review of multi-supplier inventory models in supply chain management", An update 2017. [30] X. F. Shao, "Production disruption, compensation, and transshipment policies", Omega, Vol. 74, No. 1, Jan 2018, pp. 37-49. [31] F. Morales, C. Franco and G. Mendez-Giraldo, "Dynamic inventory routing problem: Policies considering network disruptions", International Journal of Industrial Engineering Computations, Vol. 9, No. 4, October 2018, pp. 523-534. [32] M. Dada, N. C. Petruzzi, and L. B. Schwarz, "A newsvendor’s procurement problem when suppliers are unreliable", Manufacturing & Service Operations Management, Vol. 9, No. 9, August 2007, pp. 9-32.
[33] A. Schmitt, L.Snyder, and Z. J. M. Shen, "Centralization versus Decentralization: Risk Pooling, Risk Diversification, and Supply Chain Disruptions. Risk Diversification, and Supply Chain Disruptions", Omega, Vol. 52, April 2015, pp. 201-212. [34] B. Tomlin, "Disruptionmanagement strategies for short life-cycle products", Naval Research Logistics (NRL), Vol. 56, No. 4, June 2009, pp. 318-347. [35] B. Tomlin, "Impact of supply learning when suppliers are unreliable", Manufacturing & Service Operations Management, Vol. 11, No. 1, February 2009, pp. 192-209. [36] L. Qi, Z. J. M. Shen, and L. V. Snyder, "A Continuous-Review Inventory Model with Disruptions at Both Supplier and Retailer", Production and Operations Management, Vol. 18, No. 5, June 2009, pp. 516-532. [37] A. J. Schmitt, L. V. Snyder, and Z. J. M. Shen," Inventory systemswith stochastic demand and supply: Properties and approximations", European Journal of operational research, Vol. 206, No. 2, Desember 2009, pp. 313-328. [38] A. J. Schmitt,"Strategies for customer service level protection under multi-echelon supply chain disruption risk", Transportation Research Part B: Methodological, Vol. 45, No. 8, September 2011, pp. 1266-1283. [39] A. J. Schmitt and L. V. Snyder, "Infinite-horizon models for inventory control under yield uncertainty and disruptions", Computers & Operations Research, Vol. 39, No. 4, August 2010, pp. 850-862. [40] Y. He and S.Wang, "Analysis of production-inventory system for deteriorating itemswith demand disruption", International Journal of Production Research, Vol. 50, No. 16, August 2012, pp. 4580-4592. [41] A. J. Schmitt and M. Singh, "A quantitative analysis of disruption risk in a multi-echelon supply chain", International Journal of Production Economics, Vol. 139, No. 1, January 2012, pp. 22-32. [42] S. S. Ahiska, S. R. Appaji, R. E. King, and D. P. Warsingjr, "A Markov decision process-based policy characterization approach for a stochastic inventory control problem with unreliable sourcing", International Journal of Production Economics, Vol. 144, No. 2, August 2013, pp. 485-496. [43] F. Hu, C. C. Lim, and Z. Lu, "Coordination of supply chains with a flexible ordering policy under yield and demand uncertainty", International Journal of Production Economics, Vol. 146, No. 2, Desember 2013, pp. 686-693. [44] X. Yan and Y. Wang, "Supplier selection problem for a retailer under random yield", Journal of Industrial and Production Engineering, Vol. 31, No. 6, July 2014, pp. 339-349. [45] T. Sawik, "Joint supplier selection and scheduling of customer orders under disruption risks: Single vs. dual sourcing", Omega, Vol. 43, No. 2, March 2014, pp. 83-95. [46] T.Sawik, "Optimization of cost and service level in the presence of supply chain disruption risks: Single vs. multiple sourcing", Computers & Operations Research, Vol. 51, No. 1, November 2014, pp. 11-20. [47] K. K. Movahed and Z. H. Zhang, "Robust design of (s, S) inventory policy parameters in supply chains with demand and lead time uncertainties", International journal of systems science, Vol. 46, No. 12, September 2015, pp. 2258-2268. [48] V. Gupta, B. He, and S. P. Sethi, "Contingent sourcing under supply disruption and competition", International Journal of Production Research, Vol. 53, No. 10, August 2014, pp. 3006-3027. [49] T. Sawik, "On the fair optimization of cost and customer service level in a supply chain under disruption risks", Omega, Vol. 53, No. 1, June 2015, pp. 58-66. [50] N. A.Darom, H. Hishamuddin, R. Ramli, and Z. M. Nopiah, "An inventory model of supply chain disruption recovery with safety stock and carbon emission consideration", Journal of cleaner production, Vol. 197, No. 1, October 2018, pp. 1011-1021. [51] F. Lucker, S. Chorpa, and R. Seifert, "Disruption risk management in serial multi-echelon supply chains: Where to hold risk mitigation inventory and reserve capacity", Information and Operations Management, Vol. 12, No. 2, March 2019, pp. 298-315.
[52] L. D. Simchi, H. Wang, and Y. Wei, "Increasing supply chain robustness through process flexibility and inventory", Production and Operations Management, Vol. 27, No. 8, August 2018, pp. 1476-1491. [53] H. Huang, Y. He, and D. Li, "Pricing and inventory decisions in the food supply chain with production disruption and controllable deterioration", Journal of cleaner production, Vol. 180, No. 1, April 2018, pp. 280-296. [54] O. Sokolinskiy, B. Melamed, and B. Sopranzetti, "Precautionary replenishment in financially-constrained inventory systems subject to credit rolloverrisk and supply disruption", Annals of Operations Research, Vol. 271, No. 2, Desember 2018, pp. 971-997. [55] F. Lucker, R. W. Seifert, and I. Bicer, "Roles of inventory and reserve capacity in mitigating supply chain disruption risk", International Journal of Production Research, Vol. 57, No. 4, August 2018, pp. 1238-1249. [56] C. Saithong, H. T. Luong," Effect of supply disruption on inventory policy", European Journal of Industrial Engineering, Vol. 13, No. 2, March 2019, pp. 178-212. [57] J. He, F. Alavifard, D. Ivanov, and H. Jahani," A real-option approach to mitigate disruption risk in the supply chain", Omega, Vol. 88, No. c, October 2019, pp. 133-149. [58] H. Gurnani, R. Akella, and J. Lehoczky, "Supply management in assembly systems with random yield and random demand", IIE transactions, Vol. 32, No. 8, August 2000, pp. 701-714. [59] W. J. Hopp and Z. Yin, "Protecting supply chain networks against catastrophic failures. not yet published", Working Paper, Evanstone, IL: North Western, 2006. [60] A. J. Schmitt and M. Singh, "A quantitative analysis of disruption risk in a multi-echelon supply chain" International Journal of Production Economics, Vol. 139, No. 1, January 2012, pp. 22-32. ]61[علی سلماس نیا، علی زندیه و محمدرضا نامدار، "بهینه‌سازی هم‌زمان میانگین و واریانس توابعهدف در زنجیره تأمین غیرقطعی"، نشریه مدل‌سازی در مهندسی، دوره 16، شماره 53، تابستان 1397، صفحه 325-338. ]62[علی‌اکبر حسنی، "برنامه‌ریزی تصادفی دومرحله‌ای مبتنی بر روش تقریب میانگین نمونه و الگوریتم تجزیه بندرز شتاب‌یافته برای طراحی شبکه زنجیرهتأمین حلقهبسته تحت عدمقطعیت"، نشریه مدل‌سازی در مهندسی، دوره 15، شماره 49، تابستان 1396، صفحه 217-234. [63] N. Aydin and A. Murat, "A swarm intelligence based sample average approximation algorithm for the capacitated reliable facility location problem", International Journal of Production Economics, Vol. 145, No. 1, October 2013, pp.173-183. | ||
|
آمار تعداد مشاهده مقاله: 835 تعداد دریافت فایل اصل مقاله: 379 |
||