Economics Working Papers 2011, 1(1):7-56 | DOI: 10.32725/ewp.2011.001344

Fuzzy approach to supply chain management

Smolová Jaroslava, Pech Martin

During recent years, the supply chain performance management has become a key strategic consideration. Many manufacturers seek to collaborate with their suppliers and customers in order to upgrade their competitiveness and management performance. Because of complexity, uncertainty and vagueness inherent in supply chains, performance measurement using fuzzy approach was also identified as a new research direction. The main aim of the paper is focused on evaluation of logistic dimensions (sets of logistic indicators) in supply chain, where the uncertainty arises from the inability to perform adequate measurement, and deals with application of fuzzy approach, that provides a formal method for modeling imprecise, vagueness or incomplete relationships inherent in supply chains. Gathered data from questionnaires are analyzed by cluster analysis. Afterwards fuzzy methods are used evaluations of basic five dimensions, which contain several numbers of logistic indicators. The new methodology adopted from Soyer, Kabak, Asan (2007) research based on the intersection of fuzzy sets and fuzzy entropy method has been applied to evaluations in a case study. Results are afterwards modified by a applying of different membership functions, and changes of dimensions measures are analyzed. Finally supply chain modifying by adding new companies with capability of bind to supply chain are examined. New results of evaluation are compared according to new companies' membership to different clusters.

Keywords: Supply Chain, Fuzzy Sets, Fuzzy Measures, Fuzzy Entropy
JEL classification: C21, L14, L60

Received: November 21, 2012; Revised: November 21, 2012; Published: November 21, 2012  Show citation

ACS AIP APA ASA Harvard Chicago Chicago Notes IEEE ISO690 MLA NLM Turabian Vancouver
Smolová, J., & Pech, M. (2011). Fuzzy approach to supply chain management. Economics Working Papers, 1(1), 7-56. doi: 10.32725/ewp.2011.001
Share...
Download citation
  • BibTeX (.bib)
  • Bookends (.ris)
  • EasyBib (.ris)
  • EndNote (.enw)
  • EndNote 8 (.xml)
  • ISI WoS (.isi)
  • Medlars (.medlars)
  • Mendeley (.ris)
  • MODS (.xml)
  • Papers (.ris)
  • RefWorks (.txt)
  • RefManager (.ris)
  • RIS (.ris)
  • MS Word (.xml)
  • Zotero (.ris)
    • Open full article

    References

    1. ALI, Y. M., ZHANG, L. C. 1999. Surface roughness prediction of ground components using a fuzzy logic approach. Journal of materials processing technology, 1999, vol. 89-90, pp. 561-568. ΙSSN 0924-0136. Go to original source...
    2. BAI, L. F., WANG, Y. J., QU, P. X., CHEN, L. 2009. Entropy Model of Fractal Supply Chain Network with Multi-agent. In Proceedings of the 14th Youth Conference on Communication, 2009. pp. 265-267, ΙSBN 978-1-935068-01-3.
    3. BARABASI, A. L. 2002. Linked - The New Science Of Networks. Cambridge, Massachusetts: Perseus Publishing, 2002. 280 p. ΙSBN 0-7382-0667-9.
    4. BARABASI, A. L. 2005. Network theory - The emergence of the creative enterprise. Science, 2005, vol. 308, no. 5722, pp. 639-641. ΙSSN 0036-8075. Go to original source...
    5. CARRERA, D. A., MAYORGA, R. V. 2008. Supply chain management: a modular Fuzzy Inference System approach in supplier selection for new product development. Journal of Intelligent Manufacturing, 2008, vol. 19, no. 1, pp. 1-12. ΙSSN 0956-5515. Go to original source...
    6. COHEN, S., ROUSSEL, J. 2004. Strategic supply chain management: the five disciplines for top performance. New York: McGraw-Hill, 2004. 316 p. ΙSBN 978-0071432177.
    7. DE LUCA, A., TERMINI, S. 1972. Definition of nonprobabilistic entropy in setting of fuzzy sets theory. Information and Control, 1972, vol. 20, no. 4, pp. 301-312. ΙSSN 0019-9958. Go to original source...
    8. DUBOIS, D., PRADE, H. 1997. The three semantics of fuzzy sets. Fuzzy Sets and Systems, 1997, vol. 90, no. 2, pp. 141-150. ΙSSN 0165-0114. Go to original source...
    9. FAN, J. L., MA, Y. L. 2002. Some new fuzzy entropy formulas. Fuzzy Sets and Systems, 2002, vol. 128, no. 2, pp. 277-284. ΙSSN 0165-0114. Go to original source...
    10. FIALA, P. 2009. Dynamické dodavatelské sítě (1st ed.). Praha: Professional Publishing, 2009. 170 p. ΙSBN 987-80-7431-023-2.
    11. FINCH, H. 2005. Comparison of Distance Measures in Cluster Analysis with Dichotomous Data. Journal of Data Science, 2005, vol. 3, no. 1, pp. 85-100. ΙSSN 1680-743X. Go to original source...
    12. GATTORNA, J. 2006. Living Supply Chains: how to mobilize the enterprise around delivering what your customers want. London: FT Prentice Hall, 2006. 352 p. ΙSBN 978-0-273-706-14-4.
    13. GATTORNA, J. 2009. Dynamic Supply Chain Alignment. Farnham: Gower, 2009. 440 p. ΙSBN 978-0-566-08822-3.
    14. HARRISON, A., HOEK van, I. R. 2008. Logistics management and strategy: competing through the supply chain (3 rd. ed.). London: Prentice Hall, 2008. 344 p. ΙSBN 978-0-273-71276-3.
    15. HERVANI, A. A., HELMS, M. M., SARKI, J. 2005. Performance measurement for green supply chain management. Benchmarking: An International Journal, 2005, vol. 12, no. 4, pp. 330-353. ΙSSN 1463-5771. Go to original source...
    16. HUANG, T. X., YAN, J. H. 2008. The Research on Complexity of Supply Chain Inventory Management under Information Entropy. In Proceedings of International Conference on Management Science and Engineering, 2008. pp. 575-581. ΙSBN 978-0-646-50293-9.
    17. HUNG, W. L., YANG, M. S. 2006. Fuzzy entropy on intuitionistic fuzzy sets. International Journal of Intelligent Systems, 2006, vol. 21, no. 4, pp. 443-451. ΙSSN 0884-8173. Go to original source...
    18. HUSDAL, J. 2009. Is Dynamic Supply Chain Alignment the way of the future? Supply Chain Risk Research and Literature Review [online]. 2009 [cit. 2009-09-07]. Available from http://www.husdal.com/2009/09/07/is-dynamic-supply-chain-alignment-the-future/.
    19. CHANG, S. L., WANG, R. C., WANG, S. Y. 2006. Applying fuzzy linguistic quantifier to select supply chain partners at different phases of product life cycle. International Journal of Production Economics, 2006, vol. 100, no. 2, pp. 348-359. ΙSSN 0925-5273. Go to original source...
    20. CHEN, H. J., MA, F. 2009. Model for Ranking Green Supply Chain Strategies Based on MDEA. In E. S. Qi, G. Cheng, J. A. Shen, R. L. Dou (Eds.), 2009 Ieee 16th International Conference on Industrial Engineering and Engineering Management. New York: Ieee. 2009, vol 1-2 pp. 1530-1533. ISBN 978-1-4244-3670-5. Go to original source...
    21. CHEN, Y. W., LARBANI, M., LIU, C. H. 2010. Simulation of a supply chain game with multiple fuzzy goals. Fuzzy Sets and Systems, 2010, vol. 161, no. 11, pp. 1489-1510. ΙSSN 0165-0114. Go to original source...
    22. ISIK, F. 2010. An entropy-based approach for measuring complexity in supply chains. International Journal of Production Research, 2010, vol. 48, no. 12, pp. 3681-3696. ΙSSN 0020-7543. Go to original source...
    23. JU, H. M. 2009. Entropy for Interval-Valued Fuzzy Sets. In B. Y. Cao, C. Y. Zhang, T. F. Li (Eds.), Fuzzy Information and Engineering. Berlin: Springer-Verlag Berlin, 2009, vol. 1, no. 54, pp. 358-365. ISBN 978-3-540-88913-7. Go to original source...
    24. KANDA, A., DESHMUKH, S. G., ARSHINDER. 2007. Coordination in supply chains: an evaluation using fuzzy logic. Production Planning & Control, 2007, vol. 18, no. 5, pp. 420-435. ΙSSN 0953-7287. Go to original source...
    25. KARAESMEN, F., BUZACOTT, J. A., DALLERY, Y. 2002. Integrating advance order information in make-to stock production systems. IIE Transactions, 2002, vol. 35, no. 8, pp. 649-662. ΙSSN 0740-817X. Go to original source...
    26. KOSKO, B. 1986. Fuzzy entropy and conditioning. Information Sciences, 1986, vol. 40, no. 2, pp. 165-174. ΙSSN 0020-0255. Go to original source...
    27. LI, Y. F., XIE, Q. H. 2009. A Method of Identifying Supply Chain Risk Factors. In Wri World Congress on Software Engineering. Los Alamitos: Ieee Computer Soc., 2009, vol. 4, pp. 369-373. ΙSBN 978-0-7695-3570-8. Go to original source...
    28. LIANG, J. Y., CHIN, K. S., DANG, C. Y., YAM, R. C. M. 2002. A new method for measuring uncertainty and fuzziness in rough set theory. International Journal of General Systems, 2002, vol. 31, no. 4, pp. 331-342. ΙSSN 0308-1079. Go to original source...
    29. LV, X. Q., ZHOU, M. H., HUANG, Y. B., IEEE COMPUTER. 2008. Order Degree Evaluation of Large-scale Coal Enterprise Supply Chain Structure Based on Entropy. In 4th International Conference on Wireless Communications, Networking and Mobile Computing. 2008, vol. 1-31, pp. 6867-6870. ISBN 978-1-4244-2107-7. Go to original source...
    30. MARTINEZ-OLVERA, C. 2008. Entropy as an assessment tool of supply chain information sharing. European Journal of Operational Research, 2008, vol. 185, no. 1, pp. 405-417. ΙSSN 0377-2217. Go to original source...
    31. MEDASANI, S., KIM, J., KRISHNAPURAM, R. 1998. An overview of membership function generation techniques for pattern recognition. International Journal of Approximate Reasoning, 1998, vol. 19, no. 3-4, pp. 391-417. ΙSSN 0888-613X. Go to original source...
    32. MICHELS, K., KLAWONN, F., KRUSE, R., NÜRNBERGER, A. 2006. Fuzzy Control. Heidelberg: Springer Berlin, 2006. 374 p. ΙSBN 978-3-540-31765-4.
    33. MIN, H., ZHOU, G. 2002. Supply chain modeling: past present and future. Computers & Industrial Engineering, 2002, vol. 53, no. 1, pp. 231-249. ΙSSN 0360-8352. Go to original source...
    34. NOVÁK, V. 2000. Základy fuzzy modelování (1st ed.). Praha: BEN - technická literatura. 2000. 176 p. ΙSBN 80-7300-009-1.
    35. OLUGU, E., WONG, K. 2009. Supply Chain Performance Evaluation: Trends and Challenges. American Journal of Engineering and Applied Sciences, 2009, vol. 2, no. 1, pp. 202-211. ΙSSN 1941-7020. Go to original source...
    36. PECH, M., SMOLOVÁ, J. 2010. Using of fuzzy entropy as a supportive method for managing the real supply chain: case study. In 28th International Conference Mathematical Methods in Economics 2010, České Budějovice: University of South Bohemia in České Budějovice, Faculty of Economics, 2010. pp. 505-510. ΙSBN 978-80-7394-218-2.
    37. PETROVIC, D., ROY, R., PETROVIC, R. 1999. Supply chain modelling using fuzzy sets. International Journal of Production Economics, 1999, vol. 59, no. 1-3, pp. 443-453. ΙSSN 0925-5273. Go to original source...
    38. PORTER, E. M. 1979. How competitive forces shape strategy. Harvard Business Review, 1979, vol. 57, no. 2, pp. 137-145. ΙSSN 0017-8012.
    39. PORTER, E. M. 1980. Competitive Strategy: Techniques for Analyzing Industries and Competitors. New York: The Free Press, 1980. 396 p. ΙSBN 0-684-84148-7.
    40. PORTER, E. M. 1985. Competitive Advantage: Creating and Sustaining Superior Performance. New York: The Free Press, 1985. 557 p. ΙSBN 0-684-84146-0.
    41. RAJ, T. S., LAKSHMINARAYANAN, S. 2010. Entropy-Based Optimization of Decentralized Supply-Chain Networks. Industrial & Engineering Chemistry Research, 2010, vol. 49, no. 7, pp. 3250-3261. ΙSSN 0888-5885. Go to original source...
    42. ROBERTS, J. H., LATTIN, J. M. 1991. Development and testing of a model of consideration set composition. Journal of Marketing Research, 1991, vol. 28, no. 4, pp. 429-440. ΙSSN 0022-2437. Go to original source...
    43. ŘEZANKOVÁ, H., HÚSEK, D., SNÁŠEL, V. 2007. Shluková analýza dat (1st ed.). Praha: Professional Publishing, 2007. 196 p. ΙSBN 978-80-86946-26-9.
    44. SADEGH-ZADEH, K. 1999. Advances in fuzzy theory. Artificial Intelligence in Medicine, 1999, vol. 15, no. 3, pp. 309-323. ΙSSN 0933-3657. Go to original source...
    45. SHANG, X. G., JIANG, W. S. 1997. A note on fuzzy information measures. Pattern Recognition Letters, 1997, vol. 18, no. 5, pp. 425-432. ΙSSN 0167-8655. Go to original source...
    46. SHANNON, C. E., WEAVER, W. 1947. The Mathematical Theory of Communication (1st ed.). Urbana, IL: The University of Illinois Press, 1947. 117 p. ΙSBN 0-252-72548-4.
    47. SHUIABI, E., THOMSON, V., BHUIYAN, N. 2005. Entropy as a measure of operational flexibility. European Journal of Operational Research, 2005, vol. 165, no. 3, pp. 696-707. ΙSSN 0377-2217. Go to original source...
    48. SMOLOVÁ, J. 2009a. Analýza ukazatelů používaných pro hodnocení procesu skladování. Acta Universitatis Bohemiae Meridionales. The Scientific Journal for Economics, Management and Trade, 2009, vol. 12, no. 3. pp. 111-118. ΙSSN 1212-3285. Go to original source...
    49. SMOLOVÁ, J. 2009b. Logistická metrika využívaná pro hodnocení procesu dopravy. Auspicia, 2009, vol. 6, no. 2. pp. 39-41. ΙSSN 1214-4967.
    50. SOYER, A., KABAK, Ö., ASAN, U. 2007. A fuzzy approach to value and culture assessment and an application. International Journal of Approximate Reasoning, 2007, vol. 44, no. 2, pp. 182-196. ΙSSN 0888-613X. Go to original source...
    51. SPARTALIS, S., ILIADIS, L., MARIS, F. 2007. An innovative risk evaluation system estimating its own fuzzy entropy. Mathematical and Computer Modelling, 2007, vol. 46, no. 1-2, pp. 260-267. ΙSSN 0895-7177. Go to original source...
    52. SUN, W. F., YE, H. Z., IEEE COMPUTER, S. O. C. 2008. Research on Entropy Model of Order Degree of Fractal Supply Chain Network. Proceedings of the International Symposium on Electronic Commerce and Security, 2008. pp. 1006-1009. ΙSBN 978-0-7695-3258-5. Go to original source...
    53. SUZUKI, T., KODAMA, T., FURUHASHI, T., TSUTSUI, H. 2001. Fuzzy modeling using genetic algorithms with fuzzy entropy as conciseness measure. Information Sciences, 2001, vol. 136, no. 1-4, pp. 53-67. ΙSSN 0020-0255. Go to original source...
    54. TSUEN-HO, H., LING-ZHONG, L. 2006. QFD with fuzzy and entropy weight for evaluating retail customer values. Total Quality Management & Business Excellence, 2006, vol. 17, no. 7, pp. 935-958. ΙSSN 1478-3363. Go to original source...
    55. WANG, J. T., SHU, Y. F. 2005. Fuzzy decision modeling for supply chain management. Fuzzy Sets and Systems, 2005, vol. 150, no. 1, pp. 107-127. ΙSSN 0165-0114. Go to original source...
    56. WANG, T.-C., LEE, H.-D. 2009. Developing a fuzzy TOPSIS approach based on subjective weights and objective weights. Expert Systems with Applications, 2009, vol. 36, no. 5, pp. 8980-8985. ΙSSN 0957-4174. Go to original source...
    57. WILDING, R. 1998. The supply chain complexity triangle: uncertainty generation in the supply chain. International Journal of Physical Distribution and Logistics Management, 1998, vol. 28, no. 8, pp. 599-616. ΙSSN 0960-0035. Go to original source...
    58. WU, Y., FRIZELLE, G., EFSTATHIOU, J. 2007. A study on the cost of operational complexity in customer-supplier systems. International Journal of Production Economics, 2007, vol. 106, no. 1, pp. 217-229. ΙSSN 0925-5273. Go to original source...
    59. XU, J., ZENG, Q., SOCIETY, I. C. 2006. Entropy evaluation model of enterprises performance based on supply chain management theory. In APSCC: 2006 IEEE Asia-Pacific Conference on Services Computing, 2006. pp. 635-639. ΙSBN 978-0-7695-2751-2. Go to original source...
    60. XUE, X. L., SHEN, Q. P., LI, H., O'BRIEN, W. J., REN, Z. M. 2009. Improving agent-based negotiation efficiency in construction supply chains: A relative entropy method. Automation in Construction, 2009, vol. 18, no. 7, pp. 975-982. ΙSSN 0926-5805. Go to original source...
    61. YAGER, R. R. 1979. Measure of fuzziness and negation.1. membership in the unit interval. International Journal of General Systems, 1979, vol. 5, no. 4, pp. 221-229. ΙSSN 0308-1079. Go to original source...
    62. ZADEH, L. A. 1975. Fuzzy logic and approximate reasoning. Synthese, 1975, vol. 178, no. 3-4, pp. 407-428. ΙSSN 0039-7857. Go to original source...
    63. ZADEH, L. A. 1999. Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems, 1999, vol. 100, pp. 9-34. ΙSSN 0165-0114. Go to original source...
    64. ZADEH, L. A. 2008. Is there a need for fuzzy logic? Information Sciences, 2008, vol. 178, no. 13, pp. 2751-2779. ΙSSN 0020-0255. Go to original source...
    65. ZHANG, J., XU, J. 2009. Fuzzy Entropy Method for Quantifying Supply Chain Networks Complexity. Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, Springer-Verlag, 2009, vol. 5, no. 1, pp. 1690-1700. ΙSSN 978-3-642-02468-9. Go to original source...
    66. ZOU, H. X., GAO, X. Y. 2008. A Study of Supply Chain Management Efficiency Based on the Entropy Theory. In Advances in Management of Technology, Pt 2, 2008. pp. 490-495. ΙSBN 978-0-646-50024-9.

    This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, distribution, and reproduction in any medium, provided the original publication is properly cited. No use, distribution or reproduction is permitted which does not comply with these terms.


    Return to the content