Improvement Of Discrimination Power And Weight Dispersion In Multi-Criteria Data Envelopment Analysis

Lack of discrimination power and poor weight dispersion remain major issues in Data Envelopment Analysis (DEA). Since the initial multiple criteria DEA (MCDEA) model developed in the late 1990s, only goal programming approaches; that is, the GPDEA-CCR and GPDEA-BCC were introduced for solving the...

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書誌詳細
第一著者: Ghasemi, Mohammadreza
フォーマット: 学位論文
言語:英語
出版事項: 2014
主題:
オンライン・アクセス:http://eprints.usm.my/29018/
Abstract Abstract here
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author Ghasemi, Mohammadreza
author_facet Ghasemi, Mohammadreza
author_sort Ghasemi, Mohammadreza
description Lack of discrimination power and poor weight dispersion remain major issues in Data Envelopment Analysis (DEA). Since the initial multiple criteria DEA (MCDEA) model developed in the late 1990s, only goal programming approaches; that is, the GPDEA-CCR and GPDEA-BCC were introduced for solving the said problems in a multi-objective framework. Kekurangan keupayaan mendiskriminasi dan kelemahan pengagihan pemberat kekal sebagai isu utama dalam Analisis Penyampulan Data (DEA). Semenjak model DEA berbilang kriteria (MCDEA) pertama yang dibentuk pada akhir tahun 1990an, hanya pendekatan pengaturcaraangol; yakni, GPDEA-CCR dan GPDEA-BCC telah diperkenalkan bagi menyelesaikan masalah berkenaan dalam konteks berbilang kriteria.
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spelling usm-290182019-04-12T05:26:04Z http://eprints.usm.my/29018/ Improvement Of Discrimination Power And Weight Dispersion In Multi-Criteria Data Envelopment Analysis Ghasemi, Mohammadreza QA1 Mathematics (General) Lack of discrimination power and poor weight dispersion remain major issues in Data Envelopment Analysis (DEA). Since the initial multiple criteria DEA (MCDEA) model developed in the late 1990s, only goal programming approaches; that is, the GPDEA-CCR and GPDEA-BCC were introduced for solving the said problems in a multi-objective framework. Kekurangan keupayaan mendiskriminasi dan kelemahan pengagihan pemberat kekal sebagai isu utama dalam Analisis Penyampulan Data (DEA). Semenjak model DEA berbilang kriteria (MCDEA) pertama yang dibentuk pada akhir tahun 1990an, hanya pendekatan pengaturcaraangol; yakni, GPDEA-CCR dan GPDEA-BCC telah diperkenalkan bagi menyelesaikan masalah berkenaan dalam konteks berbilang kriteria. 2014 Thesis NonPeerReviewed application/pdf en http://eprints.usm.my/29018/1/IMPROVEMENT_OF_DISCRIMINATION_POWER_AND_WEIGHT_DISPERSION_IN_MULTI-CRITERIA_DATA_ENVELOPMENT_ANALSIS.pdf Ghasemi, Mohammadreza (2014) Improvement Of Discrimination Power And Weight Dispersion In Multi-Criteria Data Envelopment Analysis. PhD thesis, Universiti Sains Malaysia.
spellingShingle QA1 Mathematics (General)
Ghasemi, Mohammadreza
Improvement Of Discrimination Power And Weight Dispersion In Multi-Criteria Data Envelopment Analysis
thesis_level PhD
title Improvement Of Discrimination Power And Weight Dispersion In Multi-Criteria Data Envelopment Analysis
title_full Improvement Of Discrimination Power And Weight Dispersion In Multi-Criteria Data Envelopment Analysis
title_fullStr Improvement Of Discrimination Power And Weight Dispersion In Multi-Criteria Data Envelopment Analysis
title_full_unstemmed Improvement Of Discrimination Power And Weight Dispersion In Multi-Criteria Data Envelopment Analysis
title_short Improvement Of Discrimination Power And Weight Dispersion In Multi-Criteria Data Envelopment Analysis
title_sort improvement of discrimination power and weight dispersion in multi criteria data envelopment analysis
topic QA1 Mathematics (General)
url http://eprints.usm.my/29018/
work_keys_str_mv AT ghasemimohammadreza improvementofdiscriminationpowerandweightdispersioninmulticriteriadataenvelopmentanalysis