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Home / Uncertainty in Data Envelopment Analysis: Fuzzy and Belief Degree-Based Uncertainties
Uncertainty in Data Envelopment Analysis: Fuzzy and Belief Degree-Based Uncertainties
Paperback

Uncertainty in Data Envelopment Analysis: Fuzzy and Belief Degree-Based Uncertainties

Farhad Hosseinzadeh Lotfi (Full Professor of Mathematics, Islamic Azad University, Tehran, Iran),Masoud Sanei (Associate Professor, Department of Applied Mathematics, Islamic Azad University, Central Tehran Branch, Iran),Ali Asghar Hosseinzadeh (Assistant Professor of Applied Mathematics, Lahijan branch of Islamic Azad University, Iran),Sadegh Niroomand (Associate Professor of Industrial Engineering, Firouzabad Institute of Higher Education, Iran),Ali Mahmoodirad (Associate Professor of Applied Mathematics, Masjed-Sleiman branch of Islamic Azad University, Iran)
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Uncertainty in Data Envelopment Analysis: Fuzzy and Belief Degree-Based Uncertainties introduces methods to investigate uncertain data in DEA models, providing a deeper look into two types of uncertain DEA methods: Fuzzy DEA and Belief Degree Based Uncertainty DEA, which are based on uncertain measures. These models aim to solve problems encountered by classical data analysis in cases where inputs and outputs of systems and processes are volatile and complex, making measurement difficult. Classical data envelopment analysis (DEA) models use crisp data in order to measure inputs and outputs of a given system.

Crisp input and output data are fundamentally indispensable in the conventional DEA models. If these models contain complex-uncertain data, then they will become more important and practical for decision-makers.

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MORE INFO
Format
Paperback
Publisher
Elsevier Science & Technology
Country
United Kingdom
Date
1 June 2023
Pages
300
ISBN
9780323994446

Uncertainty in Data Envelopment Analysis: Fuzzy and Belief Degree-Based Uncertainties introduces methods to investigate uncertain data in DEA models, providing a deeper look into two types of uncertain DEA methods: Fuzzy DEA and Belief Degree Based Uncertainty DEA, which are based on uncertain measures. These models aim to solve problems encountered by classical data analysis in cases where inputs and outputs of systems and processes are volatile and complex, making measurement difficult. Classical data envelopment analysis (DEA) models use crisp data in order to measure inputs and outputs of a given system.

Crisp input and output data are fundamentally indispensable in the conventional DEA models. If these models contain complex-uncertain data, then they will become more important and practical for decision-makers.

Read More
Format
Paperback
Publisher
Elsevier Science & Technology
Country
United Kingdom
Date
1 June 2023
Pages
300
ISBN
9780323994446

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