Advanced Topics in Inverse Data Envelopment Analysis

Approaches for Handling Ratio Data

Häftad, Engelska, 2025

Av Mehdi Soltanifar, Mojtaba Ghiyasi, Farhad Hosseinzadeh Lotfi, Mohammadreza Shahriari, Iran) Soltanifar, Mehdi, PhD (Islamic Azad University, Semnan, Iran) Ghiyasi, Mojtaba, PhD (Faculty of Industrial Engineering and Management, Shahrood University of Technology, Shahrood, Iran) Lotfi, Farhad Hosseinzadeh, PhD (Science and Research Branch, Islamic Azad University, Tehran, Iran) Shahriari, Mohammadreza, PhD (South Tehran Branch, Islamic Azad University, Tehran

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Advanced Topics in Inverse Data Envelopment Analysis: Approaches for Handling Ratio Data explores and tackles the most significant challenges encountered by researchers and practitioners in decision analysis and performance evaluation. This book delves into the sophisticated realm of Ratio Data Envelopment Analysis (DEA-R), offering a thorough examination of advanced methodologies, practical examples, and insights into managing complex problems involving both non-negative and negative data. Filling crucial gaps in existing literature, this comprehensive resource focuses on the emerging field of Inverse DEA-R, equipping readers with the necessary tools and knowledge to address a wide range of challenging data types. This book serves as an essential guide for making informed and efficient decisions, guiding researchers and graduate students in computer science, applied mathematics, industrial engineering, and finance, navigating the complexities of decision analysis in today's data-driven world.

Offers an in-depth exploration of Inverse DEA-R models, making it an invaluable resource for researchers seeking to understand and apply these advanced techniques
Includes numerous practical examples and case studies across different industries demonstrating how Inverse DEA-R can be applied to real-world scenarios
Highlights potential areas for further research and development within Inverse DEA-R, encouraging readers to explore new avenues and contribute to the advancement of the field

Produktinformation

Utgivningsdatum2025-07-25
Mått152 x 229 x 15 mm
Vikt450 g
FormatHäftad
SpråkEngelska
SerieUncertainty, Computational Techniques, and Decision Intelligence
Antal sidor328
FörlagElsevier Science
ISBN9780443364884

Tillhör följande kategorier

Företagsekonomi inom Ekonomi och ledarskap
Affärsapplikationer inom Data och it
Databaser inom Data och it
Artificiell intelligens inom Data och it

Mehdi Soltanifar is an associate professor of Applied Mathematics and Operations Research. He earned his PhD from the Science and Research Branch of the Islamic Azad University (IAU), his MSc from Tehran University, and his B.S. from Birjand University. In 2008, Soltanifar joined the IAU Semnan Branch as a faculty member. His research interests encompass operations research, network flows, Multiple Attribute Decision Analysis (MADA), Data Envelopment Analysis (DEA), Analytical Hierarchy Process (AHP), and fuzzy linear programming.He currently serves as a faculty member in the Department of Mathematics at the Semnan Branch of the Islamic Azad University in Semnan, Iran.Mojtaba Ghiyasi received his PhD from the Centre of Health Economics Research (COHERE) at the University of Southern Denmark. He is currently an Associate Professor at the Faculty of Industrial Engineering and Management at Shahrood University of Technology in Shahrood, Iran. His primary research interests lie in data envelopment analysis (DEA), and the application of Operational Research approaches in the Management Sciences.Dr. Lotfi is a Full Professor of Mathematics at the Science and Research Branch, Islamic Azad University (IAU), Tehran, Iran. In 1992, he received his undergraduate degree in Mathematics at Yazd University, Yazd, Iran. He received his M.Sc in Operations Research at IAU, Lahijan, Iran in 1996 and PhD in Applied Mathematics (O.R.) at IAU, Science and Research Branch, Tehran, Iran in 2000. His major research interests are operations research and data envelopment analysis. He has published more than 300 scientific and technical papers in leading scientific journals, including European Journal of Operational Research, Computers and Industrial Engineering, Journal of the Operational Research Society, Applied Mathematics and Computation, Applied Mathematical Modelling, Mathematical and Computer Modelling, and Journal of the Operational Research Society of Japan, etc. He is Editor-in-Chief and member of editorial board of Journal of Data Envelopment Analysis and Decision Science. He is also Director-in-Charge and member of editorial board of International Journal of Industrial Mathematics. Mohammadreza Shahriari holds a Master's and PhD in Industrial Management (Operations Research) from the Islamic Azad University Science and Research Branch in Tehran, Iran. He serves as an esteemed faculty member at the South Tehran Branch of Islamic Azad University and is a valued contributor to the Research Center of Performance and Productivity Analysis at Istinye University, Istanbul, Turkey. With a focus on decision-making techniques and supply chain management, Prof. Shahriari has authored over 100 scientific and technical papers in esteemed journals such as Information Sciences, Granular Computing, Computational and Applied Mathematics, Soft Computing, Neural Computing and Applications, Computers & Industrial Engineering, Journal of Optimization in Industrial Engineering, and Applied Mathematical Sciences.In 2023, Professor Shahriari authored the book, Fuzzy Decision Analysis: Multi-Attribute Decision-Making Approach. His expertise and contributions in the field make him a respected figure in academia and research, dedicated to advancing knowledge and understanding in industrial management and operations research.

1. Managerial concepts and practical motivations2. Introduction to Data Envelopment Analysis3. DEA Models in the Presence of Negative Data4. DEA Models for Ratio Data (DEA-R Models)5. Introduction to Inverse DEA Models6. Modelling using Inverse DEA7. Inverse DEA-R Models for Engineering8. Inverse DEA-R Models for Input and Output Estimation in the Presence of Negative Data9. Inverse DEA-R Models for Mergers and Acquisitions10. Inverse DEA-R Models for Mergers and Acquisitions in the Presence of Negative Data