Management of the risk of backorders in a MTO-ATO/MTS context under imperfect requirements

Applied Mathematical Modelling

Volumn 37, Issue 16-17, 2013, Pages 8060-8078

  Guillaume, Romain ^a   Grabot, Bernard ^a   Thierry, Caroline ^a  

^a UNIVERSITÉ DE TOULOUSE   (France)

Author keywords

Fuzzy optimisation; Manufacturing; MRP; Planning

Indexed keywords

DECOUPLING POINT; EFFICIENT MANAGEMENTS; ENGINEER TO ORDERS; FUZZY MODELLING; FUZZY OPTIMISATION; MRP; PRODUCTION SYSTEM; SPECIFIC PROBLEMS;

MANUFACTURE; PLANNING; SALES; SUPPLY CHAINS;

UNCERTAINTY ANALYSIS;

EID: 84881542078     PISSN: 0307904X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.apm.2013.03.019     Document Type: Article

References (36)

1. F. Galasso, Mercé C., B. Grabot, Decision support for supply chain planning under uncertainty. in: 12th IFAC International Symposium Information Control Problems in Manufacturing (INCOM), St-Etienne, France, 2006, pp. 233-238.
2. Stadtler H., Kilger C. Supply Chain Management and Advanced Planning 2000, Springer.
3. Kolisch R. Make-to-Order Assembly Management 2001, Springer.
4. Persona A., Battini D., Manzini R., Pareschi A. Optimal safety stock levels of subassemblies and manufacturing components. Int. J. Prod. Econ. 2007, 110(1-2):147-159.
5. Dudek G. Collaborative planning in supply chains. Lect. Notes Econ. Math. Syst. 2004, 533.
6. Ireland, R., Crum, C., (2005). Supply chain Collaboration: how to implement CPFR® and other best collaborative practices, Integrated Business Management series and APICS.
7. Guillaume R., Thierry C., Grabot B. Modelling of ill-known requirements and integration in production planning. Prod. Plan. Control 2011, 22(4):336-352.
8. Grabot B., Geneste L., Reynoso Castillo G., Vérot S. Integration of uncertain and imprecise orders in the MRP method. J. Intell. Manuf. 2005, 16(2):215-234.
9. Fargier H., Thierry C. The use of possibilistic decision theory in manufacturing, planning and control: recent results in fuzzy master production scheduling. Studies in Fuzziness and Soft Computing 2000, vol. 36:45-59. Spingler-Verlag. R. Slowinski, M. Hapke (Eds.).
10. Gosling J., Naim M. Engineer-to-order supply chain management: a literature review and research agenda. Int. J. Prod. Econ. 2009, 122(2):741-754.
11. Olhager J. Strategic positioning of the order penetration point. Int. J. Prod. Econ. 2003, 85(3):319-329.
12. Adam I., Wal J. Combining make to order and make to stock. OR Spektrum 1998, 20(2):73-81.
13. Soman C.A., Pieter van Donk D., Gaalman G. Combined make-to-order and make-to-stock in a food production system. Int. J. Prod. Econ. 2004, 90(2):223-235.
14. Rajagopalan S. Make to order or make to stock: model and application. Manage. Sci. 2002, 48(2):241-256.
15. Peidro D., Mula J., Poler R., Verdegay J.L. Fuzzy optimization for supply chain planning under supply, demand and process uncertainties. Fuzzy Sets Syst. 2009, 160(18):2640-2657.
16. Zadeh L.A. Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets Syst. 1978, 1:3-28.
17. Dubois D., Prade H. Possibility Theory 1988, Plenum Press, New York.
18. Yager R.R. A procedure for ordering fuzzy subsets of the unit interval. Inform. Sci. 1981, 24:143-161.
19. Bellman R.E., Zadeh L.A. Decision-making in a fuzzy environment. Manage. Sci. 1970, 17:B-141-B-164.
20. Tavakkoli-Moghaddam R., Rabbani, M., Gharehgozli, A.H., and N. Zaerpour, A fuzzy aggregate production planning model for make-to-stock environments, in: Proceedings of the International Conference on Industrial Engineering and Engineering Management, 2007, pp. 1609-1613.
21. Mula J., Peidro D., Poler R. The effectiveness of a fuzzy mathematical programming approach for supply chain production planning with fuzzy demand. Int. J. Prod. Econ. 2010, 128:136-143.
22. Guillaume R., Kobylanski P., Zielinski P. A robust lot sizing problem with ill-known demands. Fuzzy Sets Syst. 2012, 10.1016/j.fss.2012.01.015.
23. Brindley C. Supply Chain Risk 2004, Ashgate.
24. Guillaume, R., Thierry, C., and B. Grabot, A decision support tool for procurement planning process under uncertainty, in: 18th World Congress of the International Federation of Automatic Control, Milan, 28-2 September, 2011b.
25. Mula J., Poler R., Garcia-Sabater J.P. Material requirement planning with fuzzy constraints and fuzzy coefficients. Fuzzy Sets Syst. 2007, 158(7):783-793.
26. Chen C.-T., Huang S.-F. Order-fulfillment ability analysis in the supply-chain system with fuzzy operation times. Int. J. Prod. Econ. 2006, 101:185-193.
27. Balasubramanian J., Grossmann I.E. Scheduling optimization under uncertainty an alternative approach. Comput. Chem. Eng. 2003, 27:469-490.
28. Adams F.P., Cox J.F. Manufacturing resource planning: an information systems model. Long Range Plan. 1985, 18(2):86-92.
29. Van Donselaar K., Van Den Nieuwenhof J., Visschers J. The impact of material coordination concepts on planning stability in supply chains. Int. J. Prod. Econ. 2000, 68(2):169-176.
30. Peidro D., Mula J., Jiménez M., Botella M.d.M. A fuzzy linear programming based approach for tactical supply chain planning in an uncertainty environment. Eur. J. Oper. Res. 2010, 205:65-80.
31. Dubois D., Prade H. Représentations formelles de l'incertain et de l'imprécis. Concepts et méthodes pour l'aide à la décision 2006, vol. 1. Hermès Science Publications.
32. Fortin J., Dubois D., Fargier H. Gradual numbers and their application to fuzzyinterval analysis. IEEE Trans. Fuzzy Syst. 2008, 16(2):388-402.
33. Gilboa I. Theory of Decision under Uncertainty 2009, Cambridge Books.
34. Barbera S., Jackson M. Maximin, leximin and the protective criterion. J. Econ. Theory 1988, 46(1):34-44.
35. Dubois D., Prade H. The mean value of a fuzzy number. Fuzzy Sets Syst. 1987, 24:279-300.
36. Shilkret N. Maxitive measure and integration. Indagationes Mathematicae (Proceedings) 1971, vol. 74:109-116. Elsevier.