Bi-Objective Mathematical Modeling for a Closed-Loop Supply Chain Network with Risk-Pooling and Uncertain Demands

Abstract

Today’s with increasing the competition in commercial markets and shortening the product life cycles; the variety of customer demands has been arisen; hence, these demands are confronted to uncertainty. This uncertainty has more importance with respect to the quantity and quality of the returned goods.Arisk-pooling strategy is a suitable way to consider uncertainty in demands. This paper presents new multi-objective mathematical modeling for a closed-loop supply chain network with uncertain demands using risk-pooling, in which the forward chain is consisting of suppliers, distribution centers and customers and the reverse chain encompass collection centers, recycling and recovery centers and material customers. This is a bi-objectives nonlinear integer programming model that is solved using GAMS software.

Keywords

References

 [1] Vahdani, B., Razmi, J., Tavakkoli-Moghadam, R., “Fuzzy possibilistic modeling for Closed loop recycling collection networks”, Environmental Modeling & Assessment, Volume 17, Issue6, pp 623-637, 2012.
[2] Lee, D., Dong, M., “A heuristic approach to logistics network design for end-of- lease computer products recovery”. Transportation Research Part E: Transportation Research Part E: Logistics and Transportation Review, Volume 44, Issue 3, Pages 455-474, 2008. 
[3] Pishvaee, M.S., Torabi, S.A., “A possibilistic programming approach for closed-loop supply chain network design under uncertainty”, Fuzzy Sets and Systems, 161, 2668-268, 2010.
[4] Pishvaee, M. S., Farahani, R. Z., Dullaert, W., “A memetic algorithm for bi-objective integrated forward/reverse logistics network design”. Computers & Operations Research, Volume 37, Issue 6, Pages 1100-1112, 2010.
[5] Wang, H., HSu, H., “A closed-loop logistic model with a spanning-tree based genetic algorithm”. Computers & Operations Research, Volume 37, Issue 2, Pages 376-389, 2010.
[6] Baird, N., Creating competitive advantage with service parts logistics. Inbound Logistics, 2004.
[7] فروزانفر،ف., "مدل طراحی شبکه زنجیره تأمین با در نظر گرفتن زمان تحویل، ریسک اشتراکی و موجودی تحت تقاضای نامعین"، دکتر توکلی مقدم، رضا.، دانشگاه آزاد اسلامی واحد تهران جنوب، پایان­نامه کارشناسی ارشد مهندسی صنایع، 1390.
[8] Gaur, S., Ravindran, A.R., “A bi-criteria model for the inventory aggregation problem under risk pooling”, Computers & Industrial Engineering, 51(3), 482–501, 2006.
[9] Park, S., Lee, T.-E., Sung, C.S., “A three-level supply chain network design model with risk-pooling and lead times”; Transportation Research Part E: Logistics and Transportation Review, 46(5), 563–581, 2010.
[10] Kang, J.H., Kim, Y.D., “Inventory control in a two-level supply chain with risk pooling effect”. Int. J. Production Economics 135, 116–124, (2010).
[11] Kumar., S.K., Tiwari. M.K., “Supply chain system design integrated with risk pooling”. Computers & Industrial Engineering 64, 580–588, 2013.
[12] Yang H, Schrage L., “Conditions that cause risk pooling to increase inventory”, European Journal of Operational Research; 192: 837–851, 2009.
[13] Thomas D.J., Tyworth J. E., ”Pooling lead-time risk by order splitting: A critical review”, Transportation Research Part E 2006; 42: 245–257, 2006.
[14] Arora, Jasbir. Introduction to optimum design. Academic Press, 2004.
[15] زارع مهرجردی، ی.، فریدونی، س.، امامی میبدی، ل. "ارائه یک الگوریتم ترکیبی کارا جهت حل مدل برنامه­ ریزی خطی چند­هدفه زمان­بندی مسائل تک ماشین"، نشریه بین‌المللی مهندسی صنایع و مدیریت تولید، جلد 24، شماره 1، صفحه 2-12، 1392.

Files

History

  • Receive Date: 24 December 2013
  • Revise Date: 21 January 2014
  • Accept Date: 17 February 2014
  • Publish Date: 20 June 2014

Share

How to cite

Statistics