A fuzzy association rules mining approach for modeling agility in supply chains

An approach based on fuzzy association rule mining to support the decision makers by enhancing the flexibility in making decisions for modeling agility with both tangibles and intangibles attributes is developed.

Abstract

The key issue is the ability of the integrated supply chains to deliver on competitive objectives of flexibility, profitability, quality, innovativeness, pro-activity, speed of response, cost and robustness. It is therefore imperative to discover the relationships between these agility attributes for supply chains in order to determine analytical evaluation of agility. In this paper, we develop an approach based on fuzzy association rule mining to support the decision makers by enhancing the flexibility in making decisions for modeling agility with both tangibles and intangibles attributes. Also, by checking the fuzzy classification rules, the goal of knowledge acquisition can be achieved in a framework in which evaluation of agility could be established without constraints, and consequently checked and compared in several details. Efficacy and intricacy of the proposed model for finding fuzzy association rules from the database for evaluating agility is demonstrated with the help of a numerical example.