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Growing Science » Decision Science Letters » Ranking and selection of commercial off-the-shelf using fuzzy distance based approach

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Decision Science Letters

ISSN 1929-5812 (Online) - ISSN 1929-5804 (Print)
Quarterly Publication
Volume 5 Issue 2 pp. 201-210 , 2016

Ranking and selection of commercial off-the-shelf using fuzzy distance based approach Pages 201-210 Right click to download the paper Download PDF

Authors: Rakesh Garg, R. K. Sharma, Kapil Sharma

doi 10.5267/j.dsl.2015.12.004
Crossmark

Keywords: CBSE, Commercial Off-the-Shelf (COTS), Fuzzy Distance Based Approach (FDBA), Selection Criteria

Abstract: There is a tremendous growth of the use of the component based software engineering (CBSE) approach for the development of software systems. The selection of the best suited COTS components which fulfils the necessary requirement for the development of software(s) has become a major challenge for the software developers. The complexity of the optimal selection problem increases with an increase in alternative potential COTS components and the corresponding selection criteria. In this research paper, the problem of ranking and selection of Data Base Management Systems (DBMS) components is modeled as a multi-criteria decision making problem. A ‘Fuzzy Distance Based Approach (FDBA)’ method is proposed for the optimal ranking and selection of DBMS COTS components of an e-payment system based on 14 selection criteria grouped under three major categories i.e. ‘Vendor Capabilities’, ‘Business Issues’ and ‘Cost’. The results of this method are compared with other Analytical Hierarchy Process (AHP) which is termed as a typical multi-criteria decision making approach. The proposed methodology is explained with an illustrated example.

How to cite this paper

Garg, R., Sharma, R & Sharma, K. (2016). Ranking and selection of commercial off-the-shelf using fuzzy distance based approach.Decision Science Letters , 5(2), 201-210.

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Journal: Decision Science Letters | Year: 2016 | Volume: 5 | Issue: 2 | Views: 2617 | Reviews: 0

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