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AuthorXue, Yi-Xi
AuthorYou, Jian-Xin
AuthorZhaoXufeng
AuthorLiu, Hu-Chen
Available date2021-07-05T10:58:31Z
Publication Date2016
Publication NameInternational Journal of Production Research
ResourceScopus
URIhttp://dx.doi.org/10.1080/00207543.2016.1146418
URIhttp://hdl.handle.net/10576/21089
AbstractNowadays 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. 2016 Informa UK Limited, trading as Taylor & Francis Group.
SponsorThis work was partially supported by the National Natural Science Foundation of China [grant number 71402090]; the Project funded by China Postdoctoral Science Foundation [grant number 2015T80456]; the Program for Young of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher Learning [grant number QD2015019]; Chen Guang project supported by Shanghai Municipal Education Commission and Shanghai Education Development Foundation.
Languageen
PublisherTaylor and Francis Ltd.
Subjecthesitant 2-tuple linguistic term sets
incomplete weight information
multiple criteria decision-making
QUALIFLEX
robot selection
TitleAn integrated linguistic MCDM approach for robot evaluation and selection with incomplete weight information
TypeArticle
Pagination5452-5467
Issue Number18
Volume Number54


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