Assistant Prof., Dep. of Industrial Engineering, Islamic Azad University, Science and Research Branch, Tehran, Iran
Assistant Professor, Dep. of Industrial Engineering, Iran University of Science and Technology, Tehran,
Assistant Professor, Dep. of Industrial Management, Islamic Azad University, Qazvin Branch, Qazvin, Iran
Assistant Professor, Dep. of Mathematics, Islamic Azad University, Karaj Branch, Karaj, Iran
Technology selection is an important part of management of technology. Recently Karsak and Ahiska (2005) proposed a novel common weight multiple criteria decision making (MCDM) methodology for selection of the best Advanced Manufacturing Technology (AMT) candidates based on a number of attributes. However, Amin et al. (2006), by means of a numerical example demonstrated the convergence difficulty of the Karsak and Ahiska algorithms, and then introduced an improvement model to rectify that running problem. This paper presents an MCDM-DEA methodology in order to evaluate the relative efficiency of AMTs with respect to multiple outputs and a single exact input. Using displaced ideal methodology, a practical common weight is developed and its robustness and discriminating power are illustrated via a previously reported robot evaluation problem by comparing the ranking obtained by the proposed MCDM framework with that obtained by a data envelopment analysis (DEA) classic model.