Saaty’s AHP is helpful in evaluating alternatives thanks to its effective procedure to determine the relative weights of several comparison criteria. Combining the results of expert interviews, AHP can be very useful for a company to choose a Third Party Logistics Service Provider (3PL). However, in the traditional AHP procedure, several results may be rejected when the Consistency Ratio (CR) of the respondent exceed a certain threshold. As a consequence, AHP interviews may be repeated several times with a consequent waste of time. In many industrial domains, a faster way to choose a supplier is thus appreciated. In this paper we propose a mathematical method that combines AHP, DEA and Linear Programming in order to support multi-criteria evaluation of Third Party Logistics Service Providers. The proposed model aims to get over the limitation of AHP method, merging the experts’ indications with objective judgments which originate from historical data analysis. Suppliers past performance is thus used to correct eventual errors resulting from the acceptance of interviews where the consistency ratio is high. The proposed model has been validated on the real case of an international Logistics Service Provider.
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