Selection of robotic systems in fuzzy multi criteria decision-making environment. Issue 1 (6th March 2015)

• Record Type: Journal Article
• Authors: Bairagi, Bipradas; Dey, Balaram; Sarkar, Bijan; Sanyal, Subir
• Is Part Of: International journal of computational systems engineering. Volume 2:Issue 1(2015)
• Page Start: 32
• Page End: 42
• Publication Date: 2015-03-06
• Subjects: fuzzy multi criteria decision-making -- FMCDM -- technique for order preference by similarity to ideal solution -- TOPSIS -- simple additive weighting -- SAW -- multi objective optimisation on the basis of ratio analysis -- MOORA -- robotic system selection -- system engineering; Computer science -- Periodicals; Electronic data processing -- Periodicals; System analysis -- Periodicals; 003.3
• Languages: English
• ISSNs: 2046-3391

Abstract

This paper proposes a technique for order preference by similarity to ideal solution (TOPSIS)-based fuzzy multi criteria decision-making (FMCDM) approach which is capable of dealing with tangible as well as intangible factors while selecting the best robotic system. The concept of fuzzy set theory is used to assess intangible factors. A decision matrix and a weight matrix are developed by subjective perception of decision makers. Fuzzy TOPSIS utilises subjective performance ratings to compute subjective factor measure (SFM) in terms of closeness coefficient. Objective performance ratings are utilised to determine objective factor measure (OFM). SFM and OFM along with coefficient of decision-making attitude evaluate robotic system selection index (RSSI) and aggregated robotic system selection index (ARSSI) which are the key selection parameter of robotic systems. The proposed methodology is illustrated with an example for its applicability. The result is compared with the solutions obtained by MOORA and SAW to show the effectiveness of the proposed methodology. Finally, sensitivity analysis of the problem is carried out for searching the best alternative while coefficient of decision-making attitude varies. The overall result shows that the proposed MCDM model is a very useful and effective tool for selection of robotic system.