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An MCDM-DEA approach for technology selection

Alireza Alinezhad, Ahmad Makui, Reza Kiani Mavi, Majid Zohrehbandian

发表年份
2011
引用次数
7

摘要

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 effi- ciency of AMTs with respect to multiple outputs and a single exact input. Using displaced ideal methodolo- gy, 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.

关键词

Multiple-criteria decision analysisData envelopment analysisRobustness (evolution)Ranking (information retrieval)Selection (genetic algorithm)Computer scienceMathematical optimizationOperations researchMathematicsMachine learning

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