Acta Univ. Agric. Silvic. Mendelianae Brun. 2015, 63(3), 937-945 | DOI: 10.11118/actaun201563030937

Supplier Choice Knowledge Support in the Supply Chain

Ekaterina Khitilova1, Miroslav Pokorný2
1 Department of Management and Marketing, Moravian University College Olomouc, Tř. Kosmonautů 1, 779 00 Olomouc, Czech Republic
2 Department of Informatics and Applied Mathematics, Moravian University College Olomouc, Tř. Kosmonautů 1, 779 00 Olomouc, Czech Republic

The paper focuses on the issue of choice of suppliers in the market environment. It discusses expert systems as modern methods of its computer support. The issue of supplier choice is presented and viewpoints for the formulation of the decision-making task introduced. The piece of writing furthermore pinpoints the expert character of the solution of this task, making use of the knowledge of experienced professionals. It introduces the principles of fuzzy oriented expert systems as a suitable solution of the task at hand. Language models of the expert systems formalise the high quality mental models of an experienced expert. The global decision-making task is split into partial tasks; the expert modules for their formalisation are integrated into the hierarchic structure. The paper presents the structures of language models and the implementation of the structure of expert systems in the MATLAB-Simulink program environment. Special attention is paid to the issue of supplier flexibility. The efficiency of the decision-making system is proven by the solution of a simulation exercise which represents the classification of two current and two newly contemplated suppliers with various characteristics. The results are analysed and commented on.

Keywords: supplier choice, decision-making task, knowledge system, language model, fuzzy logic, hierarchic expert system
Grants and funding:

This paper has been supported by the Czech Science Foundation, Project No. P403-12-1811: Unconventional Managerial Decision-Making Methods Development in Enterprise Economics and Public Economy.

Prepublished online: June 28, 2015; Published: August 1, 2015  Show citation

ACS AIP APA ASA Harvard Chicago IEEE ISO690 MLA NLM Turabian Vancouver
Khitilova, E., & Pokorný, M. (2015). Supplier Choice Knowledge Support in the Supply Chain. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis63(3), 937-945. doi: 10.11118/actaun201563030937
Download citation

References

  1. AKSOY, A. and OZTURK, N. 2011. Supplier selection and performance evaluation in just-in-time production environments. Expert Systems with Applications, 38: 6351-6359. DOI: 10.1016/j.eswa.2010.11.104 Go to original source...
  2. ARAZ, C. and OZKARAHAN, I. 2006. Supplier evaluation and management system for strategic sourcing based on a new multicriteria sorting procedure. International Journal of Production Economics, 106(2): 585-606. DOI: 10.1016/j.ijpe.2006.08.008 Go to original source...
  3. AWASTHI, A., CHAUHAN, S. and GOYAL, S. K. 2010. A fuzzy multicriteria approach for evaluating environmental performance of suppliers. International Journal of Production Economics, 126(2): 370-378. DOI: 10.1016/j.ijpe.2010.04.029 Go to original source...
  4. BRUNO, G., ESPOSITO, E., GENOVESE, A. and PASSARO, R. 2012. AHP-based approaches for supplier evaluation: Problems and perspectives. Journal of Purchasing & Supply Management, 18: 159-172. DOI: 10.1016/j.pursup.2012.05.001 Go to original source...
  5. BUCKLEY, J. J. and SILER, W. 2000. Fuzzy Expert Systems and Fuzzy Reasoning. Theory and Applications. United States: John Wiley & Sons Inc.
  6. CHE, Z. H. and WANG, H. S. 2008. Supplier selection and supply quantity allocation of common and non-common parts with multiple criteria under multiple products. Computers and Industrial Engineering, 55(1): 110-133. DOI: 10.1016/j.cie.2007.12.005 Go to original source...
  7. ESHTEHARDIAN, E., GHODOUSI, P. and BEJANPOUR, A. 2013. Using ANP and AHP for the Supplier Selection in the Construction and Civil Engineering Companies; Case Study of Iranian Company. KSCE Journal of Civil Engineering, 17(2): 262-270. DOI: 10.1007/s12205-013-1141-z Go to original source...
  8. KUMAR, D., SINGH, J. and PAL SINGH, O. 2013. A fuzzy logic based decision support system for evaluation of suppliers in supply chain management practices. Mathematical and Computer Modelling, 58: 1679-1695. DOI: 10.1016/j.mcm.2013.07.003 Go to original source...
  9. THE MATHWORKS. ©1994-2013. MATLAB and Simulink for Technical Computing. [online]. Retrieved from: http://www.mathworks.com. [cit. 2013-07-10].
  10. NOVÁK, V., PERFILIEVA, I. and MOČKOŘ, J. 1999. Mathematical Principles of Fuzzy Logic. Boston: Kluwer. Go to original source...
  11. OSIRO, L., LIMA Jr., F. R. and CARPINETTI, L. C. R. 2014. A fuzzy logic approach to supplier evaluation for development. Int. J. Production Economics, 153: 95-112. DOI: 10.1016/j.ijpe.2014.02.009 Go to original source...
  12. SENCER ERDEM, A. and GÖÇEN, E. 2012. Development of a decision support system for supplier evaluation and order allocation. Expert Systems with Applications, 39(5): 4927-4937. DOI: 10.1016/j.eswa.2011.10.024 Go to original source...
  13. SHU, M.-H. and WU, H.-C. 2009. Quality-based supplier selection and evaluation using fuzzy data. Computers and Industrial Engineering, 57(3): 1072-1079. DOI: 10.1016/j.cie.2009.04.012 Go to original source...
  14. RAZMI, J., RAFIEI, H. and HASHEMI, M. 2009. Designing a decision support system to evaluate and select suppliers using fuzzy analytic network process. Computers and Industrial Engineering, 57(4): 1282-1290. DOI: 10.1016/j.cie.2009.06.008 Go to original source...
  15. RUSSELL, S. and NORVIG, P. 2010. Artificial Intelligence - A Modern Approach. Prentice Hall.

This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY NC ND 4.0), which permits non-comercial 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.