logo
دوره 2، شماره 7 - ( 9-1397 )                   جلد 2 شماره 7 صفحات 40-7 | برگشت به فهرست نسخه ها


XML English Abstract Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Kolyaei M, Azar A, Rajabzadeh ghatari A. Design of An Integrated Robust Optimization Model for Closed-Loop Supply Chain and supplier and remanufacturing subcontractor selection. Journal title 2018; 2 (7) :7-40
URL: http://jde.khu.ac.ir/article-1-74-fa.html
کولیائی مریم، آذر عادل، رجب زاده قطری علی. طراحی مدل یکپارچه بهینه سازی استوار برای زنجیره تأمین با حلقه بسته و انتخاب تأمین کننده و پیمانکار. عنوان نشریه. 1397; 2 (7) :7-40

URL: http://jde.khu.ac.ir/article-1-74-fa.html


دانشگاه تربیت مدرس
چکیده:   (11966 مشاهده)
در توسعه مدل های ریاضی و بهینه سازی برای طراحی زنجیره تأمین با حلقه بسته، عدم قطعیت نهفته در طراحی شبکه، قابلیت ابزارهای بهبود را به چالش می کشد. هدف این پژوهش،  ارائه مدل ریاضی استوار برای طراحی شبکه زنجیره تأمین با حلقه بسته تحت عدم قطعیت در تقاضای مشتریان است به طوری که تصمیمات را در شبکه های مستقیم و معکوس یکپارچه کند. بدین منظور یک رویکرد دو مرحله ای پیشنهاد می شود. در مرحله اول، از یک روش فازی برای ارزیابی تأمین کننده ها بر مبنای معیارهای کیفی استفاده می شود. خروجی این مرحله ارزش هر یک از تأمین کننده ها بر حسب قطعه است که به عنوان پارامتر ورودی مرحله بعد مدل استفاده می شود. در مرحله دوم، یک مدل ریاضی برنامه ریزی خطی چند هدفه عدد صحیح مختلط پیشنهاد می شود به طوری که تعداد بهینه قطعات و محصولات را در شبکه تعیین کند. نتایج نشان می دهد که مدل پس از در نظر گرفتن هزینه هایی که استوارسازی بر سیستم تحمیل می کند، قادر به کنترل عدم قطعیت شبکه است
متن کامل [PDF 1143 kb]   (3391 دریافت)    
نوع مطالعه: كاربردي | موضوع مقاله: تخصصي
دریافت: 1396/6/19 | پذیرش: 1397/3/6 | انتشار: 1397/9/12

فهرست منابع
1. Aksoy, A., & Öztürk, N. (2011). Supplier selection and performance evaluation in just-in-time production environments. Expert Systems with Applications, 38(5), 6351-6359. [DOI:10.1016/j.eswa.2010.11.104]
2. Amin, S. H., & Razmi, J. (2009). An integrated fuzzy model for supplier management: A case study of ISP selection and evaluation. Expert Systems with Applications, 36(4), 8639-8648. [DOI:10.1016/j.eswa.2008.10.012]
3. Bertsimas, D., & Sim, M. (2004). The price of robustness. Operations Research, 52(1), 35-53. [DOI:10.1287/opre.1030.0065]
4. Cheng, M.-Y., Tsai, H.-C., & Sudjono, E. (2011). Evaluating subcontractor performance using evolutionary fuzzy hybrid neural network. International Journal of Project Management, 29(3), 349-356. [DOI:10.1016/j.ijproman.2010.03.005]
5. Clark, D., & Takahashi, Y. (2011). Quake disrupts key supply chains. The Wall Street Journal Asia, March, 12.
6. Davis, T. (1993). Effective Supply Chain Management. Sloan Management Review, 34, 35-46.
7. Du, F., & Evans, G. W. (2008). A bi-objective reverse logistics network analysis for post-sale service. Computers and Operations Research, 35(8), 2617-2634. [DOI:10.1016/j.cor.2006.12.020]
8. El-Sayed, M., Afia, N., & El-Kharbotly, a. (2010). A stochastic model for forward-reverse logistics network design under risk. Computers and Industrial Engineering, 58(3), 423-431. [DOI:10.1016/j.cie.2008.09.040]
9. Francas, D., & Minner, S. (2009). Manufacturing network configuration in supply chains with product recovery. Omega, 37(4), 757-769. http://doi.org/10.1016/j.omega.2008.07.007 [DOI:10.1016/j.omega.2008.07.007]
10. Gencer, C., & Gürpinar, D. (2007). Analytic network process in supplier selection: A case study in an electronic firm. Applied Mathematical Modelling, 31(11), 2475-2486. [DOI:10.1016/j.apm.2006.10.002]
11. Gunasekaran, A., Sarkis, J., Talluri, S., & Gunasekaran, A. (2007). A strategic model for agile virtual enterprise partner selection. International Journal of Operations & Production Management, 27(11), 1213-1234. [DOI:10.1108/01443570710830601]
12. Hadi-Vencheh, A., & Niazi-Motlagh, M. (2011). An improved voting analytic hierarchy process-data envelopment analysis methodology for suppliers selection. International Journal of Computer Integrated Manufacturing, 24(3), 189-197. [DOI:10.1080/0951192X.2011.552528]
13. Håkansson, H., & Snehota, I. (2006). No business is an island: The network concept of business strategy. Scandinavian Journal of Management, 22(3), 256-270. [DOI:10.1016/j.scaman.2006.10.005]
14. Hanafizadeh, P., & Sherkat, M. H. (2009). Designing fuzzy-genetic learner model based on multi-agent systems in supply chain management. Expert Systems with Applications, 36(6), 10120-10134. [DOI:10.1016/j.eswa.2009.01.008]
15. Hassanzadeh Amin, S., & Zhang, G. (2012). An integrated model for closed-loop supply chain configuration and supplier selection: Multi-objective approach. Expert Systems with Applications, 39, 6782-6791. [DOI:10.1016/j.eswa.2011.12.056]
16. Heidarzade, A., Mahdavi, I., & Mahdavi-amiri, N. (2016). Supplier selection using a clustering method based on a new distance for interval type-2 fuzzy sets : A case study, 38, 213-231. [DOI:10.1016/j.asoc.2015.09.029]
17. Hudymáčová, M., Benková, M., Pócsová, J., & Škovránek, T. (2010). Supplier selection based on multi-criterial AHP method. Acta Montanistica Slovaca, 15(3), 249.
18. Inderfurth, K. (2005). Impact of uncertainties on recovery behavior in a remanufacturing environment: a numerical analysis. International Journal of Physical Distribution & Logistics Management, 35(5), 318-336. [DOI:10.1108/09600030510607328]
19. Kahraman, C., & Kaya, İ. (2010). Supplier selection in agile manufacturing using fuzzy analytic hierarchy process. In Enterprise networks and logistics for agile manufacturing (pp. 155-190). Springer. [DOI:10.1007/978-1-84996-244-5_8]
20. Kim, K., Song, I., Kim, J., & Jeong, B. (2006). Supply planning model for remanufacturing system in reverse logistics environment. Computers and Industrial Engineering, 51(2), 279-287. [DOI:10.1016/j.cie.2006.02.008]
21. Klibi, W., Martel, A., & Guitouni, A. (2010). The design of robust value-creating supply chain networks: a critical review. European Journal of Operational Research, 203(2), 283-293. [DOI:10.1016/j.ejor.2009.06.011]
22. Liao, T. W. (2015). Two interval type 2 fuzzy TOPSIS material selection methods. Materials & Design, 88, 1088-1099. [DOI:10.1016/j.matdes.2015.09.113]
23. Lieckens, K., & Vandaele, N. (2007). Reverse logistics network design with stochastic lead times. Computers and Operations Research, 34(2), 395-416. [DOI:10.1016/j.cor.2005.03.006]
24. Liste, O. (2007). A generic stochastic model for supply-and-return network design, 34, 417-442. [DOI:10.1016/j.cor.2005.03.007]
25. Pati, R. K., Vrat, P., & Kumar, P. (2008). A goal programming model for paper recycling system. Omega, 36(3), 405-417. [DOI:10.1016/j.omega.2006.04.014]
26. Peidro, D., Mula, J., Poler, R., & Lario, F.-C. (2009). Quantitative models for supply chain planning under uncertainty: a review. The International Journal of Advanced Manufacturing Technology, 43(3-4), 400-420. [DOI:10.1007/s00170-008-1715-y]
27. Perić, T., Babić, Z., & Veža, I. (2013). Vendor selection and supply quantities determination in a bakery by AHP and fuzzy multi-criteria programming. International Journal of Computer Integrated Manufacturing, 26(9), 816-829. [DOI:10.1080/0951192X.2013.799778]
28. Pishvaee, M. S., Farahani, R. Z., & Dullaert, W. (2010). A memetic algorithm for bi-objective integrated forward/reverse logistics network design. Computers and Operations Research, 37(6), 1100-1112. [DOI:10.1016/j.cor.2009.09.018]
29. 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. [DOI:10.1016/j.jmsy.2010.05.001]
30. 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. [DOI:10.1016/j.apm.2010.07.013]
31. Qin, Z., & Ji, X. (2010). Logistics network design for product recovery in fuzzy environment. European Journal of Operational Research, 202(2), 479-490. [DOI:10.1016/j.ejor.2009.05.036]
32. Rezaei, J., & Ortt, R. (2012). A multi-variable approach to supplier segmentation. International Journal of Production Research, 50(16), 4593-4611. [DOI:10.1080/00207543.2011.615352]
33. 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. [DOI:10.1016/j.ejor.2005.05.032]
34. Selim, H., & Ozkarahan, I. (2008). A supply chain distribution network design model: An interactive fuzzy goal programming-based solution approach. International Journal of Advanced Manufacturing Technology, 36(3-4), 401-418. [DOI:10.1007/s00170-006-0842-6]
35. Şen, C. G., Baraçli, H., Şen, S., & Başligil, H. (2009). An integrated decision support system dealing with qualitative and quantitative objectives for enterprise software selection. Expert Systems with Applications, 36(3 PART 1), 5272-5283. [DOI:10.1016/j.eswa.2008.06.070]
36. Şen, S., Başligil, H., Şen, C. G., & Baracli, H. (2008). A framework for defining both qualitative and quantitative supplier selection criteria considering the buyer-supplier integration strategies. International Journal of Production Research, 46(7), 1825-1845. [DOI:10.1080/00207540600988055]
37. Sheu, J. B., Chou, Y. H., & Hu, C. C. (2005). An integrated logistics operational model for green-supply chain management. Transportation Research Part E: Logistics and Transportation Review, 41(4), 287-313. [DOI:10.1016/j.tre.2004.07.001]
38. Shi, J., Zhang, G., & Sha, J. (2011). Optimal production planning for a multi-product closed loop system with uncertain demand and return. Computers and Operations Research, 38(3), 641-650. [DOI:10.1016/j.cor.2010.08.008]
39. Shi, J., Zhang, G., Sha, J., & Amin, S. H. (2010). Coordinating Production and Recycling Decisions With Stochastic Demand and Return. Journal of Systems Science and Systems Engineering, 19(4), 385-407. [DOI:10.1007/s11518-010-5147-5]
40. Tam, M. C. Y., & Tummala, V. M. R. (2001). An application of the AHP in vendor selection of a telecommunications system. Omega, 29(2), 171-182. [DOI:10.1016/S0305-0483(00)00039-6]
41. Vinodh, S., Ramiya, R. A., & Gautham, S. G. (2011). Application of fuzzy analytic network process for supplier selection in a manufacturing organisation. Expert Systems with Applications, 38(1), 272-280. [DOI:10.1016/j.eswa.2010.06.057]
42. Wood, D. A. (2016). Journal of Natural Gas Science and Engineering Supplier selection for development of petroleum industry facilities , applying multi-criteria decision making techniques including fuzzy and intuitionistic fuzzy TOPSIS with fl exible entropy weighting. Journal of Natural Gas Science and Engineering, 28, 594-612. [DOI:10.1016/j.jngse.2015.12.021]
43. Wu, C., & Barnes, D. (2010). Formulating partner selection criteria for agile supply chains: A Dempster-Shafer belief acceptability optimisation approach. International Journal of Production Economics, 125(2), 284-293. [DOI:10.1016/j.ijpe.2010.02.010]
44. Zhang, G., & Ma, L. (2009). Optimal acquisition policy with quantity discounts and uncertain demands. International Journal of Production Research, 47(9), 2409-2425. [DOI:10.1080/00207540701678944]

ارسال نظر درباره این مقاله : نام کاربری یا پست الکترونیک شما:
CAPTCHA

ارسال پیام به نویسنده مسئول


بازنشر اطلاعات
Creative Commons License این مقاله تحت شرایط Creative Commons Attribution-NonCommercial 4.0 International License قابل بازنشر است.