Five crisp and fuzzy models for supply chain of an automotive manufacturing system

Fazel Zarandi, Mohammad H., Fazel Zarandi, Mohammad M. and Saghiri, S. (2007) Five crisp and fuzzy models for supply chain of an automotive manufacturing system. International Journal of Management Science and Engineering Management, 2(3), pp. 178-196. ISSN (print) 1750-9653

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Abstract

Supply Chain Management (SCM) is a new approach to production planning. It integrates the components of supply chain in a holistic manner. Modeling this large-scale system, which contains all effective enterprises in production such as raw material suppliers, part manufacturers, assembly plants, distribution organizations, and the like, is challenging for managers, engineers and researchers. This paper concentrates on supply chain system modeling with fuzzy linear programming, and fuzzy expert system for an automobile plant. First, a linear programming model is developed in such a way that while the input data is fuzzy, the constraints are crisp. In the second linear model, the coefficients of the model are crisp while the constraints are fuzzy. In the third model, we aggregate the first and the second models into one fuzzy linear programming where all constraints and coefficients are fuzzy. In each case, we compare the results with those of classical SC models. Finally, a rule based fuzzy expert system for SC is developed and the results are compared with those of the classical and fuzzy LP models. The results of the fuzzy expert system show its superiority over the former crisp and fuzzy linear programming models.

Item Type: Article
Research Area: Business and management studies
Faculty, School or Research Centre: Faculty of Business and Law
Faculty of Business and Law > Kingston Business School (Informatics and Operations Management) (until July 2013)
Depositing User: Soroosh Saghiri
Date Deposited: 16 Dec 2010 14:23
Last Modified: 16 Jul 2012 21:49
URI: http://eprints.kingston.ac.uk/id/eprint/17729

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