A fuzzy approach for modeling and design of agile supply chains using interpretive structural modeling

Supply chain agility has opened new perspectives for efficient and intelligent manufacturing. in the arena of intense global competition,analysis of supply chain enablers and their interactions between one another decide the levels of agility. previous research studies have effectively used interpretive structural modeling (ism) to study the relationships between identified enablers with the aid of structural self interaction matrix (ssim),reachability matrix (rm) & graph theoretic approach (gta). in the present paper,fuzzy agility evaluation is deployed to spot and rank agile supply chain attributes (asca) of ism identified driver enablers. the fuzzy system addressed uses linguistic variables,matlab & fuzzy technique for order preferences by similiarity to ideal solution (topsis) methods for the tabulation of fuzzy agility index (fai),fuzzy merit important index (fmii) and ranking the scores of asca. this attempt may provide firms with engrossed information in the design of agile supply chains which will be dominant competitive vehicles in future. © 2016 jordan journal of mechanical and industrial engineering. all rights reserved.