Optimal design of supply chain networks under uncertain transient demand variations

Omega

Volumn 39, Issue 3, 2011, Pages 254-272

  Georgiadis, Michael C ^a   Tsiakis, Panagiotis ^b   Longinidis, Pantelis ^a   Sofioglou, Maria K ^c  

^a UNIVERSITY OF WESTERN MACEDONIA   (Greece)

^b IBM   (United Kingdom)

^c ARISTOTLE UNIVERSITY OF THESSALONIKI   (Greece)

Author keywords

Demand uncertainty; Flexible manufacturing; Optimization; Supply chain networks

Indexed keywords

EID: 77957151962     PISSN: 03050483     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.omega.2010.07.002     Document Type: Article

References (44)

1. Shapiro JF. On the connections among activity-based costing, mathematical programming models for analyzing strategic decisions, and the resource-based view of the firm. European Journal of Operations Research 1999, 118(2):295-314.
2. Shapiro JF. Challenges of strategic supply chain planning and modelling. In: Proceedings of fourth international conference on foundations of computer-aided process operations, 2003.p. 27-34.
3. Geoffrion AM, Graves GW. Multicommodity distribution system design by Benders decomposition. Management Science 1974, 20(5):822-844.
4. Geoffrion AM, van Roy TJ. Caution: common sense planning methods can be hazardous to your corporate health. Sloan Management Review 1979, 20(4):31-42.
5. Melo MT, Nickel S, Saldanha da Gama F. Dynamic multi-commodity capacitated facility location: a mathematical modeling framework for strategic supply chain planning. Computers and Operations Research 2006, 33(1):181-208.
6. Chopra S, Meindl P. Supply chain management: strategy, planning and operations 2004, Prentice Hall, New Jersey.
7. Chandra C, Grabis J. Role of flexibility in supply chain design and modeling-introduction to the special issue. Omega 2009, 37(4):743-745.
8. Francas D, Minner S. Manufacturing network configuration in supply chains with product recovery. Omega 2009, 37(4):757-769.
9. Hallgren M, Olhager J. Flexibility configurations: empirical analysis of volume and product mix flexibility. Omega 2009, 37(4):746-756.
10. Hasuike T, Ishii H. On flexible product-mix decision problems under randomness and fuzziness. Omega 2009, 37(4):770-787.
11. Cakravastia A, Toha I, Nakamura N. A two-stage model for the design of supply chain networks. International Journal of Production Economics 2002, 80(3):231-248.
12. Xu N, Nozick L. Modeling supplier selection and the use of options contracts for global supply chain design. Computers and Operations Research 2009, 36(10):2786-2800.
13. Petersen K, Ragatz G, Monczka R. An examination of collaborative planning effectiveness and supply chain performance. The Journal of Supply Chain Management 2005, 41(2):14-25.
14. Syam SS, CÔté MJ A location-allocation model for service providers with application to not-for-profit health care organizations. Omega 2010, 38(3-4):157-166.
15. Costa AM, França PM, Lyra Filho C. Two-level network design with intermediate facilities: an application to electrical distribution systems. Omega 2011, 39(1):3-13.
16. Davis T. Effective supply chain management. Sloan Management Review 1993, 34(4):35-46.
17. Tsiakis P, Shah N, Pantelides CC. Design of multi-echelon supply chain networks under demand uncertainty. Industrial and Engineering Chemistry Research 2001, 40(16):3585-3604.
18. Guillén G, Mele B, Bagajewicz MJ, Espuña A, Puigjaner L. Multi-objective supply chain design under uncertainty. Chemical Engineering Science 2005, 60(6):1535-1553.
19. Applequist GE, Penky JF, Reklaitis G. Risk and uncertainty in managing chemical manufacturing supply chains. Computers and Chemical Engineering 2000, 24(9-10):2211-2222.
20. Papageorgiou LG. Supply chain optimisation for the process industries: advances and opportunities. Computers and Chemical Engineering 2009, 33(12):1931-1938.
21. Shah N. Pharmaceutical supply chains: key issues and strategies for optimisation. In: Proceedings of fourth international conference on foundations of computer-aided process operations, 2003. p. 73-85.
22. Al-Othman WBE, Lababidi HMS, Alatiqi IM, Al-Shayji K. Supply chain optimization of petroleum organization under uncertainty in market demands and prices. European Journal of Operational Research 2008, 189(3):822-840.
23. Pan F, Nagi R. Robust supply chain design under uncertain demand in agile manufacturing. Computers and Operations Research 2010, 37(4):668-683.
24. Gupta A, Maranas CD, McDonald CM. Mid-term supply chain planning under demand uncertainty: customer demand satisfaction and inventory management. Computers and Chemical Engineering 2000, 24(12):2613-2621.
25. Gupta A, Maranas CD. Managing demand uncertainty in supply chain planning. Computers and Chemical Engineering 2003, 27(8-9):1219-1227.
26. You F, Grossmann IE. Design of responsive supply chains under demand uncertainty. Computers and Chemical Engineering 2008, 32(12):3090-3111.
27. Hua Z, Li S, Liang L. Impact of demand uncertainty on supply chain cooperation of single-period products. International Journal of Production Economics 2006, 100(2):268-284.
28. Chen C.-L, Lee W.-C. Multi-objective optimization of multi-echelon supply chain networks with uncertain product demand and prices. Computers and Chemical Engineering 2004, 28(6-7):1131-1144.
29. Mitra K, Gudi RD, Patwardham SC, Sardar G. Mid-term supply chain planning under uncertainty: a multi-objective chance constrained programming framework. Industrial and Engineering Chemistry Research 2008, 47(15):5501-5511.
30. Amaro ACS Barbosa-Póvoa APFD. The effect of uncertainty on the optimal closed-loop supply chain planning under different partnerships structure. Computers and Chemical Engineering 2009, 33(12):2144-2158.
31. You F, Grossmann IE. Integrated multi-echelon supply chain design with inventories under uncertainty: MINLP models, computational strategies. AIChE Journal 2010, 56(2):419-440.
32. Snyder LV. Facility location under uncertainty: a review. IIE Transactions 2006, 38(7):537-554.
33. Taskin G, Fuat G. Multi-echelon inventory management in supply chains with uncertain demand and lead times: literature review from an operational research perspective. Journal Engineering Manufacture 2007, 221(10):1553-1570.
34. Peidro D, Mula J, Poler R, Lario F-C. Quantitative models for supply chain planning under uncertainty: a review. The International Journal of Advanced Manufacturing Technology 2009, 43(3-4):400-420.
35. Klibi W, Martel A, Guitouni A. The design of robust value-creating supply chain networks: a critical review. European Journal of Operational Research 2010, 203(2):283-293.
36. Wets RJ-B Challenges in stochastic programming. Mathematical Programming 1996, 75(2):115-135.
37. Ierapetritou MG, Pistikopoulos EN, Floudas CA. Operational planning under uncertainty. Computers and Chemical Engineering 1996, 20(12):1499-1516.
38. Li Z, Ierapetritou M. Process scheduling under uncertainty: review and challenges. Computers and Chemical Engineering 2008, 32(4-5):715-727.
39. Sahinidis NV. Optimization under uncertainty: state-of-the-art and opportunities. Computers and Chemical Engineering 2004, 28(6-7):971-983.
40. Schoemaker PJH Multiple scenario development: its conceptual and behavioral foundation. Strategic Management Journal 1993, 14(3):193-213.
41. Stenger AJ. Reducing inventories in a multi-echelon manufacturing firm: a case study. International Journal of Production Economics 1996, 45(1-3):239-249.
42. Vanston JH, Frisbie WP, Lopreato SC, Boston DL Alternate scenario planning. Technological Forecasting and Social Change 1977, 10(2):159-180.
43. Karuppiah R, Martín M, Grossmann IE. A simple heuristic for reducing the number of scenarios in two-stage stochastic programming. Computers and Chemical Engineering 2010, 34(8):1246-1255.
44. Rosenthal RE. GAMS: a user's guide 2008, GAMS Development Corporation, Washington, DC.