research-article

Design alternative assessment and selection: : A novel Z-cloud rough number-based BWM-MABAC model

Authors:

Guangquan Huang,

Witold Pedrycz,

Dragan Pamucar,

Luis MartínezAuthors Info & Claims

Volume 603, Issue C

Pages 149 - 189

https://doi.org/10.1016/j.ins.2022.04.040

Published: 01 July 2022 Publication History

Abstract

Design alternative assessment is vital in product development since it directly influences the directions of subsequent design and manufacturing activities. The alternative assessment information chiefly depends on experts’ subjective perceptions and preferences, which include several types of uncertainty, such as intrapersonal perception ambiguousness, personal judgment reliability, and interpersonal preference inconsistency. However, previous studies usually just consider one of the various uncertainties, which may affect their effectiveness. To fill this gap, we develop an integrated design alternative assessment model integrating Z-cloud rough numbers (ZCRNs), best-worst method (BWM), and multi-attributive border approximation area comparison (MABAC). First, to fully handle various uncertainties, a new concept of ZCRN is developed by combining the benefits of cloud model in addressing intrapersonal uncertainty, the merits of Z-numbers in reflecting judgmental reliability, and the strengths of rough numbers in handling interpersonal uncertainty. Some arithmetic operating rules, Minkowski-type distance, comparison measure, correlation measure, and aggregation operators for ZCRNs are also introduced. Furthermore, a ZCRN-BWM method and a ZCRN-MABAC method are developed to calculate criteria weights and rank design alternatives. Finally, a case study, sensitivity analysis on two parameters and a normalization method, and several comparisons are performed to elaborate and validate the developed model.

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Design alternative assessment and selection: A novel Z-cloud rough number-based BWM-MABAC model

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cover image Information Sciences: an International Journal

Information Sciences: an International Journal Volume 603, Issue C

Jul 2022

289 pages

ISSN:0020-0255

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Elsevier Inc.

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Elsevier Science Inc.

United States

Publication History

Published: 01 July 2022

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https://dl.acm.org/doi/10.3233/JIFS-236124
Jiang JLiu XWang ZDing WZhang SXu H(2024)Large group decision-making with a rough integrated asymmetric cloud model under multi-granularity linguistic environmentInformation Sciences: an International Journal10.1016/j.ins.2024.120994678:COnline publication date: 1-Sep-2024
https://dl.acm.org/doi/10.1016/j.ins.2024.120994
Liao HLiu FXiao YWu ZKazimieras Zavadskas E(2024)A survey on Z-number-based decision analysis methods and applicationsInformation Sciences: an International Journal10.1016/j.ins.2024.120234663:COnline publication date: 1-Mar-2024
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