A Parameter Reduction-Based Decision-Making Method with Interval-Valued Neutrosophic Soft Sets for the Selection of Bionic Thin-Wall Structures

Author:

Zhang Honghao12ORCID,Wang Lingyu1,Wang Danqi3ORCID,Huang Zhongwei1,Yu Dongtao1,Peng Yong4ORCID

Affiliation:

1. Key Laboratory of High Efficiency and Clean Mechanical Manufacture (Ministry of Education), School of Mechanical Engineering, Shandong University, Jinan 250061, China

2. Key Laboratory of Transportation Industry for Transport Vehicle Detection, Diagnosis and Maintenance Technology, Jinan 250061, China

3. College of Automotive and Mechanical Engineering, Changsha University of Science and Technology, Changsha 410114, China

4. Key Laboratory of Traffic Safety on Track of Ministry of Education, School of Traffic and Transportation Engineering, Central South University, Changsha 410083, China

Abstract

Bio-inspired thin-wall structures with excellent mechanical properties, high-energy absorption capabilities, and a desirable lightweight level have been extensively applied to the passive safety protection of transportation and aerospace. Collaboration matching and the selection of optional structures with different bionic principles considering the multiple attribute evaluation index and engineering preference information have become an urgent problem. This paper proposes a parameter reduction-based indifference threshold-based attribute ratio analysis method under an interval-valued neutrosophic soft set (IVNS-SOFT) to obtain the weight vector of an evaluation indicator system for the selection of bionic thin-wall structures, which can avoid the problem of an inadequate subjective evaluation and reduce redundant parameters. An IVNS-SOFT-based multi-attributive border approximation area comparison (MABAC) method is proposed to obtain an optimal alternative, which can quantify uncertainty explicitly and handle the uncertain and inconsistent information prevalent in the expert system. Subsequently, an application of five bio-inspired thin-wall structures is applied to demonstrate that this proposed method is valid and practical. Comparative analysis, sensitivity analysis, and discussion are conducted in this research. The results show that this study provides an effective tool for the selection of bionic thin-wall structures.

Funder

Natural Science Foundation of Shandong

Science & Technology Plan of Yantai City Project

Natural Science Foundation of Hunan Province

Major Projects of CRRC

China Postdoctoral Science Foundation Funded Project

Key Laboratory of Transportation Industry for Transport Vehicle Detection, Diagnosis and Maintenance Technology

Hunan Science Foundation for Distinguished Young Scholars of China

Publisher

MDPI AG

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