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Pourmahmoud, Jafar, Abbasi, Ahad, Ghaffari-Hadigheh, Alireza. (1404). Network Data Envelopment Analysis and Uncertainty in Decision-Making‎: ‎A Three-Stage Model Based on Liu's Uncertainty Theory. فصلنامه علمی زیست فناوری گیاهان زراعی, (), -. doi: 10.30473/coam.2025.73893.1293
Jafar Pourmahmoud; Ahad Abbasi; Alireza Ghaffari-Hadigheh. "Network Data Envelopment Analysis and Uncertainty in Decision-Making‎: ‎A Three-Stage Model Based on Liu's Uncertainty Theory". فصلنامه علمی زیست فناوری گیاهان زراعی, , , 1404, -. doi: 10.30473/coam.2025.73893.1293
Pourmahmoud, Jafar, Abbasi, Ahad, Ghaffari-Hadigheh, Alireza. (1404). 'Network Data Envelopment Analysis and Uncertainty in Decision-Making‎: ‎A Three-Stage Model Based on Liu's Uncertainty Theory', فصلنامه علمی زیست فناوری گیاهان زراعی, (), pp. -. doi: 10.30473/coam.2025.73893.1293
Pourmahmoud, Jafar, Abbasi, Ahad, Ghaffari-Hadigheh, Alireza. Network Data Envelopment Analysis and Uncertainty in Decision-Making‎: ‎A Three-Stage Model Based on Liu's Uncertainty Theory. فصلنامه علمی زیست فناوری گیاهان زراعی, 1404; (): -. doi: 10.30473/coam.2025.73893.1293

Network Data Envelopment Analysis and Uncertainty in Decision-Making‎: ‎A Three-Stage Model Based on Liu's Uncertainty Theory

Control and Optimization in Applied Mathematics
مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 02 مرداد 1404    اصل مقاله (585.62 K)
نوع مقاله: Research Article
شناسه دیجیتال (DOI): 10.30473/coam.2025.73893.1293
نویسندگان
Jafar Pourmahmoud* ؛ Ahad Abbasi؛ Alireza Ghaffari-Hadigheh
Department of Applied Mathematics‎, ‎Azarbaijan Shahid Madani University‎, ‎Tabriz‎, ‎Iran.
چکیده
Data Envelopment Analysis (DEA) is a well-established methodology for assessing the efficiency of decision-making units‎. ‎In complex systems comprising multiple interconnected subsections‎, ‎Network DEA provides a structured framework for efficiency evaluation‎. ‎However‎, ‎traditional DEA models rely on the assumption of deterministic data‎, ‎which inadequately reflects the inherent uncertainty present in real-world scenarios‎. ‎Traditional uncertainty-handling methods‎, ‎such as fuzzy logic‎, ‎stochastic models‎, ‎and interval-based techniques‎, ‎often fail when there is limited historical data and when expert opinions significantly influence the dataset‎. ‎To address these limitations‎, ‎this study introduces an uncertain network DEA model based on Liu’s uncertainty theory‎, ‎facilitating a more accurate assessment of efficiency under conditions of data imprecision‎. ‎The proposed model is designed for three interconnected subsections and is further extended into a generalized multi-stage framework‎, ‎allowing it to adapt to increasingly complex systems‎. ‎Its effectiveness and practical applicability are demonstrated through two numerical case studies in the banking industry‎, ‎highlighting its capacity to support decision-making under uncertainty‎. ‎The findings emphasize the model's potential to enhance efficiency evaluation methods‎, ‎particularly in environments characterized by limited and uncertain data‎.

تازه های تحقیق
  • Introduces a novel network DEA framework integrating Liu’s uncertainty theory to effectively address data imprecision and inherent uncertainty.
  • Extends the conventional three-stage network DEA model into a flexible, multi-stage (p-stage) framework capable of modeling increasingly complex, interconnected systems under uncertainty.
  • Demonstrates the model’s robustness and practical utility through two comprehensive real-world case studies in the banking industry, emphasizing its applicability with limited and subjective data.
  • Highlights the model’s superior ability to incorporate expert opinions and subjective judgments, improving decision-making in environments with scarce or imprecise data.
  • Validates the framework’s capacity for accurate efficiency assessment and resource allocation despite data uncertainty, supporting strategic decision-making in diverse complex systems.
  • Showcases the potential of the proposed approach to enhance traditional DEA methodologies by effectively capturing data variability and uncertainty in multi-agent and multi-stage environments.
کلیدواژه‌ها
Uncertainty theory‎؛ ‎Network DEA‎؛ ‎Efficiency‎؛ ‎Banking system
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