The application of fuzzy Delphi and fuzzy inference system in supplier ranking and selection


1 Department of Mechanical Engineering, Faculty of Engineering, University of Malaya, 50603, Kuala Lumpur, Malaysia

2 Department of Mechanical Engineering, Shiraz University, 71936, Shiraz, Iran


In today’s highly rival market, an effective
supplier selection process is vital to the success of any
manufacturing system. Selecting the appropriate supplier is
always a difficult task because suppliers posses varied
strengths and weaknesses that necessitate careful evaluations
prior to suppliers’ ranking. This is a complex process
with many subjective and objective factors to consider
before the benefits of supplier selection are achieved. This
paper identifies six extremely critical criteria and thirteen
sub-criteria based on the literature. A new methodology
employing those criteria and sub-criteria is proposed for the
assessment and ranking of a given set of suppliers. To handle
the subjectivity of the decision maker’s assessment, an
integration of fuzzy Delphi with fuzzy inference system has
been applied and a new ranking method is proposed for
supplier selection problem. This supplier selection model
enables decision makers to rank the suppliers based on three
classifications including ‘‘extremely preferred’’, ‘‘moderately
preferred’’, and ‘‘weakly preferred’’. In addition, in
each classification, suppliers are put in order from highest
final score to the lowest. Finally, the methodology is verified
and validated through an example of a numerical test bed.