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Abbasi, Masomeh, Ghomashi, Abbas, Shahghobadi, Saeed. (1401). Finding common weights in DEA using a compromise solution approach. , 10(2), 63-72. doi: 10.30495/ijdea.2022.68441.1165
Masomeh Abbasi; Abbas Ghomashi; Saeed Shahghobadi. "Finding common weights in DEA using a compromise solution approach". , 10, 2, 1401, 63-72. doi: 10.30495/ijdea.2022.68441.1165
Abbasi, Masomeh, Ghomashi, Abbas, Shahghobadi, Saeed. (1401). 'Finding common weights in DEA using a compromise solution approach', , 10(2), pp. 63-72. doi: 10.30495/ijdea.2022.68441.1165
Abbasi, Masomeh, Ghomashi, Abbas, Shahghobadi, Saeed. Finding common weights in DEA using a compromise solution approach. , 1401; 10(2): 63-72. doi: 10.30495/ijdea.2022.68441.1165

Finding common weights in DEA using a compromise solution approach

International Journal of Data Envelopment Analysis
دوره 10، شماره 2، مرداد 2022، صفحه 63-72  XML اصل مقاله (827.59 K)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.30495/ijdea.2022.68441.1165
نویسندگان
Masomeh Abbasi email 1؛ Abbas Ghomashi1؛ Saeed Shahghobadi2
1Department of mathematics, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran.
2Department of Mathematics, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran.
چکیده
The weights generated by the common weights approach provide a common criterion for ranking the decision-making units (DMUs) in data envelopment analysis (DEA). Existing common weights models in DEA are either very complicated or unable to produce a full ranking for DMUs. This paper proposes a new compromise solution model to seek a common set of weights for full ranking for DMUs. The maximum inefficiency scores calculated from the standard DEA model are regarded as the anti-ideal solution for the DMUs to avoid. A common set of weights that produces the vector of inefficiency scores for the DMUs furthest to the anti-ideal solution is sought. The discrimination power of the new model is tested using two numerical examples and its potential application for fully ranking DMUs is illustrated.
کلیدواژه‌ها
common weights؛ data envelopment analysis؛ ranking
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