Optimizing supply chain management using fuzzy approach

Journal of Manufacturing Technology Management

Volumn 17, Issue 6, 2006, Pages 737-749

  Gunasekaran, N ^a   Rathesh, S ^b   Arunachalam, S ^c   Koh, S C L ^d  

^a KUMARAGURU COLLEGE OF TECHNOLOGY   (India)

^b Fine Jewellery (I) Ltd   (India)

^c UNIVERSITY OF EAST LONDON   (United Kingdom)

^d UNIVERSITY OF SHEFFIELD   (United Kingdom)

Author keywords

Decision making; Fuzzy logic; Monte Carlo simulation; Quality function deployment; Supply chain management

Indexed keywords

COMPUTER SIMULATION; DECISION MAKING; FUZZY CONTROL; MONTE CARLO METHODS; OPTIMIZATION; PRODUCT DESIGN; QUALITY FUNCTION DEPLOYMENT; RANDOM NUMBER GENERATION;

CASE STUDY; MULTI-OBJECTIVE MODEL; RANDOM NUMBER TESTING METHODS; SUPPLY CHAIN MANAGEMENT;

INVENTORY CONTROL;

EID: 33746597442     PISSN: 1741038X     EISSN: None     Source Type: Journal    
DOI: 10.1108/17410380610678774     Document Type: Article

References (16)

1. Abebe, A.J., Guinot, V. and Solomatine, D.P. (2000), "Fuzzy alpha-cut vs Monte Carlo techniques in assessing uncertainty in model parameters", Proc. of 4-th International Conference on Hydroinfomatics, Iowa City.
2. Appelqvist, P., Lehtonen, J.M. and Kokkonen, J. (2004), "Modelling in product and supply chain design: literature survey and case study", Journal of Manufacturing Technology Management, Vol. 15 No. 7, pp. 675-86.
3. Franceschini, F. and Rosseto, S. (2002), "QFD: an interactive algorithm for the prioritization of product's technical design characteristics", Integrated Manufacturing Systems, Vol. 13, pp. 69-75.
4. Jain, V., Tiwari, M.K. and Chan, F.T.S. (2004), "Evaluation of the supplier performance using an evolutionary fuzzy-based approach", Journal of Manufacturing Technology Management, Vol. 15 No. 8, pp. 735-44.
5. Lowen, R. (1996), Fuzzy Set Theory, Kluwer Academic Publishers, London.
6. Vanegas, L.V. and Labib, A.W. (2001a), "Application of new fuzzy-weighted average (NFWA) method to engineering design evaluation", International Journal of Production Research, Vol. 39, pp. 1147-62.
7. Vanegas, L.V. and Labib, A.W. (2001b), "A fuzzy quality function deployment (FQFD) model for deriving optimum targets", International Journal of Production Research, Vol. 39, pp. 99-120.
8. Bojadziev, G. and Bojadziev, B. (1997), Fuzzy Logic for Business, Finance and Management, World Scientific Publication, Singapore.
9. Erol, I. and Ferrel, W.G. Jr (2003), "A methodology for selection problems with multiple conflicting objectives and both qualitative and quantitative criteria", International journal of Production Economics, Vol. 86, pp. 187-99.
10. Khoo, L.P. and Ho, N.C. (1996), "Framework of a fuzzy quality function deployment system", International Journal of Production Research, Vol. 34 No. 2, pp. 299-311.
11. Kumar, R. and Midha, P.S. (2001), "A QFD based methodology for evaluating a company PDM requirements for collaborative product development", Industrial Management & Data Systems, Vol. 10 No. 3, pp. 126-31.
12. Ohdar, R. and Ray, P.K. (2004), "Performance measurement and evaluation of suppliers in supply chain: an evolutionary fuzzy-based approach", Journal of Manufacturing Technology Management, Vol. 15 No. 8, pp. 723-34.
13. Power, D. (2005), "Implementation and use of B2B-enabling technologies: five manufacturing cases", Journal of Manufacturing Technology Management, Vol. 16 No. 5, pp. 554-72.
14. Ross, T.J. (1995), Fuzzy Logic with Engineering Applications, McGraw-Hill International Edition, Singapore.
15. Wang, J. (1999), "Fuzzy out ranking approach to prioritize design requirements in quality function deployment", International Journal of Production Research, Vol. 37 No. 4, pp. 899-916.
16. Weber, C., Werner, H. and Deubel, T. (2003), "A different view on product data management/product life-cycle management and its future potentials", Journal of Engineering Design, Vol. 14 No. 4, pp. 447-64.