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Developing fuzzy expert systems models for supply chain complex problem: a comparison with linear programming

Developing fuzzy expert systems models for supply chain complex problem: a comparison with linear programming
Developing fuzzy expert systems models for supply chain complex problem: a comparison with linear programming

Supply Chain Management (SCM) system endeavors to achieve global optimum solution(s) in supply network problems. SCM systems are mostly large-scale and are recognized as complex systems. This paper concentrates on supply chain system modeling with fuzzy expert systems (FES). The FES is developed based on the knowledge and information of the experts in an automotive supply chain. Then the results are compared with those of the fuzzy linear programming models in this area. The results of the FES show its superiority over linear programming models especially in CPU times and satisfaction of decision makers of results and their understandability.

1098-7584
1375-1380
Fazel Zarandi, M.H.
4c7a5aeb-95ee-42fc-bd02-e91c8f501c47
Saghiri, Soroosh
6bfd600c-bdd1-4dde-9f33-d3f138e85e9d
Fazel Zarandi, M.H.
4c7a5aeb-95ee-42fc-bd02-e91c8f501c47
Saghiri, Soroosh
6bfd600c-bdd1-4dde-9f33-d3f138e85e9d

Fazel Zarandi, M.H. and Saghiri, Soroosh (2006) Developing fuzzy expert systems models for supply chain complex problem: a comparison with linear programming. In 2006 IEEE International Conference on Fuzzy Systems. pp. 1375-1380 . (doi:10.1109/FUZZY.2006.1681889).

Record type: Conference or Workshop Item (Paper)

Abstract

Supply Chain Management (SCM) system endeavors to achieve global optimum solution(s) in supply network problems. SCM systems are mostly large-scale and are recognized as complex systems. This paper concentrates on supply chain system modeling with fuzzy expert systems (FES). The FES is developed based on the knowledge and information of the experts in an automotive supply chain. Then the results are compared with those of the fuzzy linear programming models in this area. The results of the FES show its superiority over linear programming models especially in CPU times and satisfaction of decision makers of results and their understandability.

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More information

Published date: 2006
Venue - Dates: 2006 IEEE International Conference on Fuzzy Systems, , Vancouver, BC, Canada, 2006-07-16 - 2006-07-21

Identifiers

Local EPrints ID: 472774
URI: http://eprints.soton.ac.uk/id/eprint/472774
DOI: doi:10.1109/FUZZY.2006.1681889
ISSN: 1098-7584
PURE UUID: dc4970a3-416d-4abc-8f03-f0779ccb697b
ORCID for Soroosh Saghiri: ORCID iD orcid.org/0000-0003-3100-3207

Catalogue record

Date deposited: 19 Dec 2022 17:30
Last modified: 17 Mar 2024 04:17

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Contributors

Author: M.H. Fazel Zarandi
Author: Soroosh Saghiri ORCID iD

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