Open Access
MATEC Web Conf.
Volume 81, 2016
2016 5th International Conference on Transportation and Traffic Engineering (ICTTE 2016)
Article Number 06001
Number of page(s) 5
Section Supply Chains
Published online 25 October 2016
  1. Ko M, Tiwari A, Mehnen J, “A review of soft computing applications in supply chain management” Applied Soft Computing, 10, (2010), pp. 661–674 [CrossRef]
  2. Botzheim J, Földesi P, “Fuzzy neural network with novel computation of fuzzy exponent in the sigmoid functions.” In: Proceedings of the 8th International Symposium on Management Engineering, ISME 2011, Taipei, Taiwan, pp. 285–291
  3. Botzheim J, Cabrita C, Kóczy LT, Ruano AE, “Fuzzy rule extraction by bacterial memetic algorithms.” In: Proceedings of the 11th World Congress of International Fuzzy Systems Association, IFSA 2005, Beijing, China, pp. 1563–1568
  4. Bozarth CC, Warsing DP, Flynn BB, Flynn EJ, “The impact of supply chain complexity on manufacturing plant performance.” Journal of Operations Management 27(1) (2009), pp. 78–93 [CrossRef]
  5. Dubois A, Hulthén K, Pedersen AC “Supply chains and interdependence: a theoretical analysis.” Journal of Purchasing and Supply Management 10(1) (2004), pp. 3–9 [CrossRef]
  6. Gál L, Botzheim J, Kóczy LT, Ruano AE, “Applying bacterial memetic algorithm for training feedforward and fuzzy flip-flop based neural networks.” In: Proceedings of the 2009 IFSA World Congress and 2009 EUSFLAT Conference, IFSA-EUSFLAT 2009, Lisbon, Portugal, pp. 1833–1838
  7. Hecht-Nielsen R, Neurocomputing. Addison-Wesley (1990)
  8. Moscato P, “On evolution, search, optimization, genetic algorithms and martial arts: Towards memetic algorithms.” Tech. Rep. Caltech Concurrent Computation Program, Report. 826, (1989) California Institute of Technology, Pasadena, California, USA
  9. Nawa NE, Furuhashi T: “Fuzzy system parameters discovery by bacterial evolutionary algorithm.” IEEE Transactions on Fuzzy Systems 7(5) (1999), pp. 608–616 [CrossRef]
  10. Németh P, “Flexibility in supply chains” Acta Technica Jaurinensis Series Logistica, 1(2) (2008) pp.371–379.
  11. Németh P, “Ellátási láncok hatékony irányítása multi kritériumos teljesítmény méréssel” (in Hungarian). Ph.D. thesis, 2009, Széchenyi István University, Győr, Hungary
  12. Németh P, Földesi P, Botzheim J, “Enhancing warehouse performance at a global company” In: Proceedings of Knowledge Globalization Conference, Boston, Massachusetts, (October 2011), pp. 7–19.
  13. Németh P, Földesi P, Csík Á, “The concept of logistic space in the modelling of supply chain performance” In: Proceedings of the 22nd Annual Production and Operations Management Society Conference, Reno, Nevada, (May 2011)
  14. Zurada JM, Introduction to Artificial Neural Systems, West Publishing Co., St. Paul (1992)
  15. Bhagwat R, Sharma MK, “Performance measurement of supply chain management: A balanced scorecard approach”, Computers & Industrial Engineering 53(1) (2007) pp. 43–62 [CrossRef]

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