Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/160596
Title: Evaluating biological inspiration for biologically inspired design: an integrated DEMATEL-MAIRCA based on fuzzy rough numbers
Authors: Zhu, Guoniu
Ma, Jin
Hu, Jie
Keywords: Engineering::Mechanical engineering
Issue Date: 2021
Source: Zhu, G., Ma, J. & Hu, J. (2021). Evaluating biological inspiration for biologically inspired design: an integrated DEMATEL-MAIRCA based on fuzzy rough numbers. International Journal of Intelligent Systems, 36(10), 6032-6065. https://dx.doi.org/10.1002/int.22541
Journal: International Journal of Intelligent Systems 
Abstract: Biological inspiration evaluation has been widely acknowledged as one of the most important phases in biologically inspired design (BID) as it substantially determines the direction of the following-up design activities. However, it is inherently an interdisciplinary assessment, which includes both the engineering domain and the biological systems. Due to the lack of knowledge at the early stage of product design, the risk assessments mainly depend on experts' subjective judgments, which values are vague, imprecise, and even inconsistent. How to objectively evaluate the biological inspiration under such uncertain and interdisciplinary scenarios remains an open issue. To bridge such gaps, this study proposes a fuzzy rough number extended multi-criteria group decision-making (MCGDM) to evaluate the biological inspiration for BID. A fuzzy rough number is introduced to represent the individual decision maker's risk assessment and aggregate respective evaluation values within the decision-making group. A fuzzy rough number extended decision-making trial and evaluation laboratory is presented to determine the criteria weights and a fuzzy rough number extended multi-attribute ideal real comparative analysis is proposed to rank the candidate biological inspirations. Experimental results and comparative analysis validate the superiority of the proposed MCGDM in handling the subjectivity and uncertainty in biological inspiration evaluation.
URI: https://hdl.handle.net/10356/160596
ISSN: 0884-8173
DOI: 10.1002/int.22541
Schools: School of Mechanical and Aerospace Engineering 
Rights: © 2021 Wiley Periodicals LLC. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:MAE Journal Articles

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