پیوندهای مفید
اخبار و اعلانات
آمار
| تعداد نشریات | 163 |
| تعداد شماره‌ها | 6,762 |
| تعداد مقالات | 72,831 |
| تعداد مشاهده مقاله | 131,701,160 |
| تعداد دریافت فایل اصل مقاله | 103,456,114 |
Resilient Supply Network Design of a Two Stage Supply Chain and Risk Analysis Using Stochastic Programming (A Case Study of GPPS Supply Chain) | ||
| Industrial Management Journal | ||
| مقاله 10، دوره 9، شماره 1، 2017، صفحه 189-216 اصل مقاله (601.46 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22059/imj.2017.208998.1007078 | ||
| نویسندگان | ||
| Ali Mohaghar1؛ Nima Garusi Mokhtarzadeh2؛ Mohammad Modarres Yazdi3؛ Moein Hajimaghsoudi* 4 | ||
| 1Prof. of Industrial Management, Tehran University, Tehran, Iran | ||
| 2Assistant Prof. of Industrial Management, Tehran University, Tehran, Iran | ||
| 3Prof., Faculty of Industrial Engineering, Sharif University, Tehran, Iran | ||
| 4Ph.D. Candidate of Industrial Management, University of Tehran, Tehran, Iran | ||
| چکیده | ||
| This paper proposes a multi-period resilient supply network model for a two stage supply chain in which one of the main raw materials should be bought from different suppliers and various products should be produced for customers in several manufacturer production sites. We used two-stage stochastic programming provided that the customers have uncertain demands and the suppliers propose uncertain prices from time to time. In contrast with previous researches, we considered disruption risks of supply, mitigation strategies and contingency plans against risks to improve the resilience of our supply network. Also, to increase the authenticity of our model, we consider the production planning in each production site simultaneously. The supply network design was analyzed from a risk-neutral and a risk-averse decision maker point of view. To illustrate the applicability of our proposed approach, computational results of using this model in a real-life case was presented. Finally, to investigate the influence of cost parameter changes on the results of the model, we performed a sensitive analysis. | ||
| کلیدواژه‌ها | ||
| Resilient supply network؛ Risk consideration؛ Scenario reduction؛ Two-stage stochastic program | ||
| مراجع | ||
|
دری، ب.، حمزهای، ا. (1389). تعیین استراتژی پاسخ به ریسک در مدیریت ریسک بهوسیلۀ تکنیک ANP (مطالعۀ موردی: پروژۀ توسعۀ میدان نفتی آزادگان شمالی)، نشریۀ مدیریت صنعتی، 2 (4)، 92-75. سلسبیل، م.، شفیعا، م. ع.، پیشوایی، م.، شهانقی، ک. (1394). برنامهریزی تاکتیکی استوار زنجیرة تأمین جهانی سه سطحی تحت شرایط اختلال تحریم با در نظر گرفتن عمر قفسهای (مطالعۀ موردی: زنجیرۀ تأمین دارو)، نشریۀ مدیریت صنعتی، 7(2)، 332-305. Ahmed, S. (2006). Convexity and decomposition of mean risk stochastic programs. Mathematical Programming, 106(3), 433-446.
Ayhan, M.B. & Kilic, H.S. )2015(. A two stage approach for supplier selection problem in multi item/ multi-supplier environment with quantity discounts. Computers & Industrial Engineering, 85, 1-12.
Ayhan, M.B. (2013). Fuzzy TOPSIS Application for supplier selection problem. International Journal of Information Business and Management, 5 (2), 159-174.
Burt, D.N., Dobler, D.W. & Starling, S.L. (2004). World Class Supply Management: The Key to Supply Chain Management (Seventh ed). McGrawHill, Boston, MA.
Carbone, J., (1999). Evaluation programs determine top suppliers. Purchasing, 127 (8), 31–35.
Cárdenas-Barrón, L.E., González-Velarde, J.L. & Treviño-Garza, G. )2015(. A new approach to solve the multi-product multi-period inventory lot sizing with supplier selection problem, Computers & Operations Research, 64, 225-232.
Eppen, G.D., Martin, R.K. & Schrage, L. (1989). OR practice- a scenario approach to capacity planning. Operations Research, 37(4), 517–527.
Fábián, C.I. (2013). Computational aspects of risk-averse optimization in two-stage stochastic models. Available in: http://www.optimization-online.org/DB_ FILE/2012 /08/3574.pdf.
Ghodsypour, S.H. & O’Brien, C. (1998). A Decision Support System for Supplier Selection Using an Integrated Analytic Hierarchy Process and Linear Programming. International Journal of Production Economics, 56-57, 199-212.
Govindan, K. & Fattahi, M. (2015). Investigating risk and robustness measures for supply chain network design under demand uncertainty: A case study of glass supply chain. International Journal of Production Economics, 183, 680-699.
Haldar, A. & Ray, A. )2014(. Resilient supplier selection under a fuzzy environment. International Journal of Management Science and Engineering Management, 9(2), 147-156.
Handfield, R.B. & McCormack, K. (2008). Supply Chain Risk Management: Minimizing Disruptions in Global Sourcing. Series on Resource Management. New York, Auerbach Publications.
Heidarzade, A., Mahdavi, I. & Mahdavi-Amiri, N. )2015(. Supplier Selection Using a Clustering Method Based on a New Distance for Interval Type-2Fuzzy Sets: A Case Study. Applied Soft Computing Journal, 38(c), 213-231.
Hou, A. Z. Zeng, and L. Zhao, "Coordination with a backup supplier through buy-back contract under supply disruption," Transportation Research Part E: Logistics and Transportation Review, 46, 881-895. Inderfurth, K., Kelle, P. & Kleber, R. (2013). Dual sourcing using capacity reservation and spot market: Optimal procurement policy and heuristic parameter determination. European Journal of Operational Research, 225(2), 298-309.
Inderfurth, K. & Kelle, P. )2011(. Capacity reservation under spot market price uncertainty. International Journal of Production Economics, 133(1), 272-279.
Keyvanloo, A., Kimiagari, A.M. & Esfahanipour, A. (2014). Risk analysis of sourcing problem using stochastic programming, Industrial Engineering, 21(3), 1034-1043.
Krajewsld, L.J. & Ritzman, L.P. (1996). Operations Management Strategy and Analysis. London, Addison-Wesley Publishing Co.
Linthorst, M.M. & Telgen, J. (2007(. Public Purchasing Future: Buying from Multiple Sources. Advancing Public Procurement: Practices, Innovation and Knowledge-Sharing. Academics Press, Boca Raton, FL., 471–482.
Manuj, I. & Mentzer, J.T. (2008). Global supply chain risk management strategies. International Journal of Physical Distribution & Logistics Management, 38 (3), 192–223.
Meena P.L., Sarmah S.P. & Sarkar S.A. )2011(. Sourcing decisions under risks of catastrophic event disruptions. Transportation Research Part E: Logistics and Transportation Review, 47(6), 1058–1074.
Moghaddam, K. )2015(. Fuzzy multi-objective model for supplier selection and order allocation in reverse logistics systems under supply and demand uncertainty. Expert Systems with Applications, 42, 6237-6254.
Moritz, S. & Pibernik, R. (2008). The optimal number of suppliers in the presence of volume discounts and different compensation potentials – an analytical and numerical analysis. Working Paper. European Business School Research.
Nam, S.H., Vitton, J. & Kurata, H. (2009). Robust supply base management: determining the optimal number of suppliers utilized by contractors. International Journal of Production Economics, 134(2), 333-343.
Neiger, D., Rotaru, K., & Churilov, L. (2009). Supply chain risk identification with value-focused process engineering. Journal of Operations Management, 27, 154-168.
Norrman, A. & Jansson, U. (2004). Ericsson’s proactive supply chain risk management approach after a serious sub-supplier accident. International Journal of Physical Distribution & Logistics Management, 34 (5), 434-456.
Noyan N. )2012(. Risk-averse two-stage stochastic programming with an application to disaster management. Computers and Operations Research. (39), 541–559.
Oke, A. & Gopalakrishnan, M. (2009). Managing disruptions in supply chains: A case study of a retail supply chain. International Journal of Production Economics, 118, 168–174.
Pazhani, S., Ventura, J.A. & Mendoza, A. )2015(. A Serial Inventory System with Supplier Selection and Order Quantity Allocation considering Transportation Costs. Applied Mathematical Modelling,40(1), 612-634.
Rawls, C.G. & Turnquist, M.A. (2010). Pre-positioning of emergency supplies for disaster response. Transportation Research Part B: Methodological, 44(4), 521–534.
Ross, S.M. (2007). Introduction to Probability Models. Academic Press.
Ruiz-Torres, A., Mahmoodi, F. & Zeng, A. (2013). Supplier selection model with contingency planning for supplier failures. Computers & Industrial Engineering, 66(2), 374-382.
Sawik, T. (2011). Selection of supply portfolio under disruption risks, Omega, vol, 39, 194-208.
Sawik, T. (2013). Selection of resilient supply portfolio under disruption risks. Omega, 41, 259–269.
Schoenherr, T., Modi, S.B., Benton, W.C., Carter, C.R., Choi, T.Y., Larson, P.D., Leenders, M.R., Mabert, V.A., Narasimhan & R., Wagner, S.M. ( 2012). Research opportunities in purchasing and supply management. International Journal of Production Research, 50, 4556–4579.
Shahidehpour, M & Li, T. (2007). Stochastic Security-Constrained Unit Commitment. Ieee Transactions On Power Systems, 22, 800-811.
Sonmez, M. (2006). A review and critique of supplier selection process and practices. Working Paper. European Business School Research, Loughborough University.
Tang, C. S. (2006). Perspectives in supply chain risk management. International Journal of Production Economics, 103, 451-488.
Tomlin, B. (2006). On the value of mitigation and contingency strategies for managing supply chain disruption risks. Management Science, 52 (5), 639–657.
Torabi, S.A., Baghersad, M. & Mansouri, S.A. (2015). Resilient supplier selection and order allocation under operational and disruption risks. Transportation Research Part E, 79, 22–48.
Trevelen, M. & Schweikhart, S.B. (1988). A risk/benefit analysis of sourcing strategies: single vs multiple sourcing. Journal of Operations Management, 7 (4), 93–114.
Trikman, P. & McCormack, K. (2009). Supply chain risk in turbulent environments – A conceptual model for managing supply chain network risk. International Journal of Production Economics, 119, 247–258.
Weber, C.A., Current J.R. & Benton, W.C. (1991). Vendor Selection Criteria and Methods. European Journal of Operational Research, 50(1), 2-18.
Yu, H., Zeng, A.Z. & Zhao, L. (2009). Single or dual sourcing: decision-making in the presence of supply chain disruption risks. Omega, 37 (4), 788–800.
| ||
|
آمار تعداد مشاهده مقاله: 782 تعداد دریافت فایل اصل مقاله: 1,054 |
||
سامانه مدیریت نشریات علمی. قدرت گرفته از سیناوب