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Reseach Article

A Composite Weight based Multiple Attribute Decision Support System for the Selection of Automated Guided Vehicles

by Vishram B. Sawant, Suhas S. Mohite
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 70 - Number 19
Year of Publication: 2013
Authors: Vishram B. Sawant, Suhas S. Mohite
10.5120/12173-8222

Vishram B. Sawant, Suhas S. Mohite . A Composite Weight based Multiple Attribute Decision Support System for the Selection of Automated Guided Vehicles. International Journal of Computer Applications. 70, 19 ( May 2013), 8-16. DOI=10.5120/12173-8222

@article{ 10.5120/12173-8222,
author = { Vishram B. Sawant, Suhas S. Mohite },
title = { A Composite Weight based Multiple Attribute Decision Support System for the Selection of Automated Guided Vehicles },
journal = { International Journal of Computer Applications },
issue_date = { May 2013 },
volume = { 70 },
number = { 19 },
month = { May },
year = { 2013 },
issn = { 0975-8887 },
pages = { 8-16 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume70/number19/12173-8222/ },
doi = { 10.5120/12173-8222 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:33:15.536030+05:30
%A Vishram B. Sawant
%A Suhas S. Mohite
%T A Composite Weight based Multiple Attribute Decision Support System for the Selection of Automated Guided Vehicles
%J International Journal of Computer Applications
%@ 0975-8887
%V 70
%N 19
%P 8-16
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper proposes a decision support system which integrates the objective weights of importance of the attributes as well as the subjective preferences of the decision maker to decide the composite weights of importance of the attributes. Using fuzzy set theory the qualitative attributes are converted into the quantitative attributes. Based on this model, a decision support system AGVSEL is developed for the selection of AGVs. AGVs are ranked by using the technique for order preference by similarity to ideal solution (TOPSIS), block TOPSIS and modified synthetic evaluation method (M-TOPSIS). The effectiveness of the support system is demonstrated with an illustrative example. The computational results obtained enable evaluation and selection of an appropriate AGV. Sensitivity analysis reveals that at a moderate value of interpolating factor rank transition takes place for topmost position thereby achieving better insight into the complex interplay of subjective and objective weights. Finally, the results of the proposed approach are compared with the results obtained by published methods. Thus, the proposed weight method with AGVSEL system improves decision making in MADM environment.

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Index Terms

Computer Science
Information Sciences

Keywords

Multiple attribute decision making automated guided vehicle decision support system TOPSISifx