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

Ghasemi, Mohammadreza (2014) Improvement Of Discrimination Power And Weight Dispersion In Multi-Criteria Data Envelopment Analysis. PhD thesis, Universiti Sains Malaysia.

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    Abstract

    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.

    Item Type: Thesis (PhD)
    Subjects: Q Science > QA Mathematics > QA1 Mathematics (General)
    Divisions: Pusat Pengajian Sains Matematik (School of Mathematical Sciences)
    Depositing User: Administrator Automasi
    Date Deposited: 09 Jun 2015 14:40
    Last Modified: 09 Jun 2015 14:40
    URI: http://eprints.usm.my/id/eprint/29018

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