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
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Online Access:http://eprints.usm.my/60885/1/YOUSEF%20ZEHI%20ROKHSANEH%20-%20TESIS24.pdf
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spelling my-usm-ep.608852024-07-31T04:27:53Z Robust Optimization Approach In Data Envelopment Analysis Models: Extension To The Cases With Uncertain Production Trade-offs, Integer Data And Negative Data. 2023-08 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 http://eprints.usm.my/60885/ http://eprints.usm.my/60885/1/YOUSEF%20ZEHI%20ROKHSANEH%20-%20TESIS24.pdf application/pdf en public phd doctoral Universiti Sains Malaysia Pusat Pengajian Sains Matematik
institution Universiti Sains Malaysia
collection USM Institutional Repository
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
qualification_name Doctor of Philosophy (PhD.)
qualification_level Doctorate
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.
granting_institution Universiti Sains Malaysia
granting_department Pusat Pengajian Sains Matematik
publishDate 2023
url http://eprints.usm.my/60885/1/YOUSEF%20ZEHI%20ROKHSANEH%20-%20TESIS24.pdf
_version_ 1811772856116183040