Journal
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
Volume 54, Issue 18, Pages 5452-5467Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/00207543.2016.1146418
Keywords
robot selection; hesitant 2-tuple linguistic term sets; QUALIFLEX; multiple criteria decision-making; incomplete weight information
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Funding
- National Natural Science Foundation of China [71402090]
- China Postdoctoral Science Foundation [2015T80456]
- Program for Young of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher Learning [QD2015019]
- Chen Guang project - Shanghai Municipal Education Commission
- Shanghai Education Development Foundation
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Nowadays selecting the most suitable robot is a difficult task for manufacturing firms due to increase in production demands and availability of various robot models. Robot evaluation and selection can be regarded as a multiple criteria decision-making (MCDM) problem and three key issues are the assessment of robots, the determination of criteria weights and the prioritisation of alternatives. This paper aims to propose an integrated model based on hesitant 2-tuple linguistic term sets and an extended QUALIFLEX approach for handling robot selection problems with incomplete weight information. The new model can not only manage uncertain and imprecise assessment information of decision-makers with the aid of hesitant 2-tuple linguistic term sets, but also derive the important weights of criteria objectively when the weight information is incompletely known. Moreover, based on the extended QUALIFLEX algorithm, the priority orders of robots can be clearly determined and a more reasonable and credible solution can be yielded in a particular industrial application. Finally, a robot selection case study is carried out, and comparative experiments indicate the practicality and effectiveness of the proposed integrated linguistic MCDM approach.
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