مقاله

a practical common weight scalarizing function approach for technology selection

چکیده

abstract. a practical common weight scalarizing function methodology with an improved discriminating power for technology selection is introduced. the proposed scalarizing function methodology enables the evaluation of the relative efficiency of decision-making units (dmus) with respect to multiple outputs and a single exact input with common weights. its robustness and discriminating power are illustrated via a previously reported robot evaluation problem by comparing the ranking obtained by the proposed scalarizing function framework with that obtained by the dea classic model (ccr model) and minimax method (karsak & ahiska,2005). because the number of efficient dmus is reduced so discriminating power of our approach is higher than previous approaches and because spearman’s rank correlation between the ranks obtained from our approach and minimax approach is high therefore robustness of our approach is justified.

اسناد مشابه

  • Practical common weights scalarizing function approach for efficiency analysis

    مقاله۲۰۱۰Journal of Optimization in Industrial EngineeringAhmad Makui, Alireza Alinezhad, Majid Zohrehbandian, Reza Kiani Mavi

    A characteristic of Data Envelopment Analysis (DEA) is to allow individual decision making units (DMUs) to select the factor weights which are the most advantageous for them in calculating their efficiency scores. This flexibility in selecting the weights, on the other hand, dete

  • practical common weights scalarizing function approach for efficiency analysis

    مقاله۲۰۱۰journal of optimization in industrial engineeringalireza alinezhad, reza kiani mavi, majid zohrehbandian, ahmad makui

    a characteristic of data envelopment analysis (dea) is to allow individual decision making units (dmus) to select the factor weights which are the most advantageous for them in calculating their efficiency scores. this flexibility in selecting the weights, on the other hand, dete

  • practical common weights scalarizing function approach for efficiency analysis

    مقالهjournal of optimization in industrial engineeringalireza alinezhad, department of industrial engineering, islamic azad university of qazvin, qazvin, iran reza kiani mavi, department of industrial management, islamic azad university of qazvin, qazvin, iran majid zohrehbandian, department of industrial management, islamic azad university of qazvin, qazvin, iran ahmad makui

    a characteristic of data envelopment analysis (dea) is to allow individual decision making units (dmus) to select the factor weights which are the most advantageous for them in calculating their efficiency scores. this flexibility in selecting the weights, on the other hand, dete

  • A Practical Common Weight Scaling Function Approach for Technology Selection

    سند علمی۲۰۱۴Mousa AMINI, Alireza ALINEZHAD

    A practical common weight scaling function methodology with an improved discriminating power for technology selection is introduced. The proposed scaling function methodology enables the evaluation of the relative efficiency of decision-making units (DMUs) with respect to multipl

  • Practical common weights MOLP approach for efficiency analysis

    مقاله۲۰۰۸Journal of Industrial Engineering, InternationalA Alinezhad, A Makui, M Zohrehbandian

    A characteristic of data envelopment analysis (DEA) is to allow individual decision making units (DMUs) to select the factor weights that are the most advantages for them in calculating their efficiency scores. This flexibility in selecting the weights, on the other hand, deters

  • practical common weights molp approach for efficiency analysis

    مقاله۲۰۰۸journal of industrial engineering, internationala makui, a alinezhad, m zohrehbandian

    a characteristic of data envelopment analysis (dea) is to allow individual decision making units (dmus) to select the factor weights that are the most advantages for them in calculating their efficiency scores. this flexibility in selecting the weights, on the other hand, deters