Uncertain Range Directional Measure Model under Deep Uncertainty: A Robust Convex Programming Approach
سال انتشار: 1400
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 476
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شناسه ملی سند علمی:
CSIEM02_807
تاریخ نمایه سازی: 27 تیر 1400
چکیده مقاله:
Conventional data envelopment analysis (DEA) models cannot deal with negative and uncertain values. Accordingly, the main objective of current study is to present a novel robust data envelopment analysis (RDEA) approach that is capable to be used in the presence of negative values and uncertain data. Notably, to propose RDEA approach, range directional measure (RDM) model and robust convex programming approach are employed. Finally, the applicability and efficacy of the proposed robust range directional measure (RRDM) model is demonstrated by assessing the relative performance of ۱۵ stocks from Tehran stock exchange. The results indicate on the efficacy of the presented RRDM model for performance measurement of DMUs in the presence of negative values and uncertainty environment.
کلیدواژه ها:
نویسندگان
Pejman Peykani
School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran
Seyed Ahmad Edalatpanah
Department of Industrial Engineering, Ayandegan Institute of Higher Education, Tonekabon, Iran
Seyed Esmaeil Najafi
Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
Alireza Amirteimoori
Department of Applied Mathematics, Rasht Branch, Islamic Azad University, Rasht, Iran
Ali Ebrahimnejad
Department of Mathematics, Qaemshahr Branch, Islamic Azad University, Qaemshahr, Iran