International Journal of Industrial Engineering & Technology (IJIET) ISSN 2277-4769 Vol.2, Issue 2 Sep 2012 1-15 © TJPRC Pvt. Ltd., A HYBRID APPROACH BASED ON FUZZY DEA AND BSC TO MEASURE THE EFFICIENCY OF SUPPLY CHAIN; REAL CASE OF INDUSTRY HAMID KAZEMKHANLOU 1 & HAMIDREZA AHADI 2 1 Graduate student of Transportation Engineering, School of Railway Engineering Iran University of Science & Technology, Tehran, Iran 2 Assistant Professor, School of Railway Engineering, Iran University of Science & Technology,Tehran, Iran ABSTRACT Performance evaluation plays an important role in determining faults and difficulties of any supply chain as well as attempting to increase capabilities and improve activities. Data envelopment analysis (DEA), as a non-parametric method, has been one of the most important and significant management tools for measuring output or efficiency. In fact, in a real evaluation problem input and output data of entities evaluated often fluctuate. These fluctuating data can be represented as linguistic variables characterized by fuzzy numbers for reflecting a kind of general feeling or experience of experts. Based on the fundamental CCR model, a fuzzy DEA model is proposed to deal with the efficiency evaluation problem with the given fuzzy input and output data. . In this paper, we propose a method to utilize balanced score card (BSC) as a tool for designing performance evaluation indices of an supply chain. The integrated BSC-FDEA has been applied as an empirical case for Iranian dairy industry supply chains and the results are analyzed. KEYWORDS: Data envelopment analysis (DEA); Balanced scorecard; Performance Evaluation; Fuzzy DEA; Fuzzy linear programming INTRODUCTION Measuring the efficiency of any supply chain has become an interesting issue among interested researchers. Data envelopment analysis (DEA) initially proposed by Charnes et al. [3] is a non- parametric technique for measuring and evaluating the relative efficiencies of a set of entities, called decision-making units (DMUs), with the common inputs and outputs. Examples include school, hospital, library and, more recently, whole economic and society systems, in which outputs and inputs are always multiple in character. Most of DEA papers make an assumption that input and output data are crisp ones without any variation. In fact, inputs and outputs of DMUs are ever-changeful. For example, for evaluating operation efficiencies of airlines, seat-kilometers available, cargo-kilometers available, fuel and labor are regarded as the inputs and passenger-kilometers performed as the output [5]. It is common sense that these inputs and output are easy to change because of weather, season, operating state and so