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Robust Optimization Approach In Data Envelopment Analysis Models: Extension To The Cases With Uncertain Production Trade-offs, Integer Data And Negative Data.

Data envelopment analysis (DEA) is a popular performance measurement technique and since it was first introduced, DEA models have been extensively applied in real-world managerial problems. One of the challenges in applying DEA models in real-world problems is uncertainty and inaccuracy in data whic...

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Main Author:	Rokhsaneh, Yousef Zehi
Format:	Thesis
Language:	English
Published:	2023
Subjects:	QA1 Mathematics (General)
Online Access:	http://eprints.usm.my/60885/1/YOUSEF%20ZEHI%20ROKHSANEH%20-%20TESIS24.pdf http://eprints.usm.my/60885/
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id	my.usm.eprints.60885
record_format	eprints
spelling	my.usm.eprints.60885 http://eprints.usm.my/60885/ Robust Optimization Approach In Data Envelopment Analysis Models: Extension To The Cases With Uncertain Production Trade-offs, Integer Data And Negative Data. Rokhsaneh, Yousef Zehi QA1 Mathematics (General) Data envelopment analysis (DEA) is a popular performance measurement technique and since it was first introduced, DEA models have been extensively applied in real-world managerial problems. One of the challenges in applying DEA models in real-world problems is uncertainty and inaccuracy in data which can be due to error in measurement, calculation, prediction etc. As uncertainty is an inevitable factor in many optimization problems, therefore the uncertainty in data should be taken into consideration to ensure reliable optimal solutions and benchmarking. Robust optimization is one of the most recent approaches for handling uncertainty in DEA models which immunize the uncertain parameters over a pre-specified uncertainty set to determine an optimal solution which is guaranteed to be the best for all or most of the possible realizations of the uncertain parameters. Applying robust optimization approach in DEA models resulted to Robust DEA field which is a relatively young yet growing field in DEA, introduced in 2008. The goal of this thesis is to fulfil some of the theoretical and practical gaps in robust DEA field. The previous works on robust DEA models only considered inputs and outputs data to be uncertain, thus one of the objectives of this thesis is to assess the effect of uncertainty in the other involved parameters in the optimization such as weights assigned to inputs and outputs and production trade-offs. Moreover, a comparative analysis between the proposed robust DEA model and other approaches of handling uncertainty in data such as interval DEA will be provided. 2023-08 Thesis NonPeerReviewed application/pdf en http://eprints.usm.my/60885/1/YOUSEF%20ZEHI%20ROKHSANEH%20-%20TESIS24.pdf Rokhsaneh, Yousef Zehi (2023) Robust Optimization Approach In Data Envelopment Analysis Models: Extension To The Cases With Uncertain Production Trade-offs, Integer Data And Negative Data. PhD thesis, Universiti Sains Malaysia.
institution	Universiti Sains Malaysia
building	Hamzah Sendut Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Sains Malaysia
content_source	USM Institutional Repository
url_provider	http://eprints.usm.my/
language	English
topic	QA1 Mathematics (General)
spellingShingle	QA1 Mathematics (General) Rokhsaneh, Yousef Zehi Robust Optimization Approach In Data Envelopment Analysis Models: Extension To The Cases With Uncertain Production Trade-offs, Integer Data And Negative Data.
description	Data envelopment analysis (DEA) is a popular performance measurement technique and since it was first introduced, DEA models have been extensively applied in real-world managerial problems. One of the challenges in applying DEA models in real-world problems is uncertainty and inaccuracy in data which can be due to error in measurement, calculation, prediction etc. As uncertainty is an inevitable factor in many optimization problems, therefore the uncertainty in data should be taken into consideration to ensure reliable optimal solutions and benchmarking. Robust optimization is one of the most recent approaches for handling uncertainty in DEA models which immunize the uncertain parameters over a pre-specified uncertainty set to determine an optimal solution which is guaranteed to be the best for all or most of the possible realizations of the uncertain parameters. Applying robust optimization approach in DEA models resulted to Robust DEA field which is a relatively young yet growing field in DEA, introduced in 2008. The goal of this thesis is to fulfil some of the theoretical and practical gaps in robust DEA field. The previous works on robust DEA models only considered inputs and outputs data to be uncertain, thus one of the objectives of this thesis is to assess the effect of uncertainty in the other involved parameters in the optimization such as weights assigned to inputs and outputs and production trade-offs. Moreover, a comparative analysis between the proposed robust DEA model and other approaches of handling uncertainty in data such as interval DEA will be provided.
format	Thesis
author	Rokhsaneh, Yousef Zehi
author_facet	Rokhsaneh, Yousef Zehi
author_sort	Rokhsaneh, Yousef Zehi
title	Robust Optimization Approach In Data Envelopment Analysis Models: Extension To The Cases With Uncertain Production Trade-offs, Integer Data And Negative Data.
title_short	Robust Optimization Approach In Data Envelopment Analysis Models: Extension To The Cases With Uncertain Production Trade-offs, Integer Data And Negative Data.
title_full	Robust Optimization Approach In Data Envelopment Analysis Models: Extension To The Cases With Uncertain Production Trade-offs, Integer Data And Negative Data.
title_fullStr	Robust Optimization Approach In Data Envelopment Analysis Models: Extension To The Cases With Uncertain Production Trade-offs, Integer Data And Negative Data.
title_full_unstemmed	Robust Optimization Approach In Data Envelopment Analysis Models: Extension To The Cases With Uncertain Production Trade-offs, Integer Data And Negative Data.
title_sort	robust optimization approach in data envelopment analysis models: extension to the cases with uncertain production trade-offs, integer data and negative data.
publishDate	2023
url	http://eprints.usm.my/60885/1/YOUSEF%20ZEHI%20ROKHSANEH%20-%20TESIS24.pdf http://eprints.usm.my/60885/
_version_	1806443598712930304
score	13.211869

Robust Optimization Approach In Data Envelopment Analysis Models: Extension To The Cases With Uncertain Production Trade-offs, Integer Data And Negative Data.

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