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Optimal selection of E‐learning websites using multiattribute decision‐making approaches
Author(s) -
Garg Rakesh
Publication year - 2017
Publication title -
journal of multi‐criteria decision analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.462
H-Index - 47
eISSN - 1099-1360
pISSN - 1057-9214
DOI - 10.1002/mcda.1612
Subject(s) - selection (genetic algorithm) , computer science , machine learning , artificial intelligence , operations research , engineering
A computational quantitative model based on weighted Euclidean distance‐based approximation and complex proportional assessment has been developed for the evaluation, selection, and ranking of various E‐learning websites in ascending or descending order based on their Euclidean distance value from the optimal website. The E‐learning website with rank 1 is considered the optimal selection on the particular dataset under consideration. The problem of the E‐learning website Selection, Evaluation and Ranking is modeled as a multiattribute decision‐making problem in which various interrelated attributes collectively termed as ranking criteria are identified to make the evaluation of available alternatives. In this research, 5 most popular E‐learning websites related to the C programming language for the software development have been considered to show the utility of developed model. Further, the concept of methodology validation strengthens this research by comparing the obtained results with the existing multiattribute decision‐making approach as analytical hierarchy process method.