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.

[img]
Preview
PDF
Download (258kB) | Preview

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 06:40
Last Modified: 12 Apr 2019 05:26
URI: http://eprints.usm.my/id/eprint/29018

Actions (login required)

View Item View Item
Share