A Probability-based Fuzzy Multi-objective Optimization for Material Selection

被引:1
作者
Zheng, Maosheng [1 ]
Yu, Jie [2 ]
机构
[1] Northwest Univ, Sch Chem Engn, 229,Taibai North Rd, Xian 710069, Shaanxi, Peoples R China
[2] Northwest Univ, Coll Life Sci, 229,Taibai North Rd, Xian 710069, Shaanxi, Peoples R China
来源
TEHNICKI GLASNIK-TECHNICAL JOURNAL | 2024年 / 18卷 / 02期
关键词
fuzzy; intersection; multi-objective optimization; probability; utility;
D O I
10.31803/tg-20230515054622
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In the present paper, a rational fuzzy multi-objective optimization for material selection is developed in respect of probabilistic method for multi-objective optimization, which agrees with the viewpoint of system theory for the whole optimization of a system and is the novelty of this work. The basic ideas and algorithms of fuzzy theory together with probability theory are taken as the cornerstone to perform the formulation. In the treatment, the intersection of the membership function of fuzzy numbers of alternative material performance and the membership function of fuzzy numbers of desired material performance is used as the utility of the material performance index. Thereafter, the utility of each material performance index is further used to conduct the assessment of its partial preferable probability and formulate the multi-objective optimization by means of probability theory. Moreover, a typical example is presented to provide the rational process of the probabilistic fuzzy multi-objective optimization for material selection.
引用
收藏
页码:178 / 182
页数:5
相关论文
共 16 条
[1]  
[Anonymous], 2004, Fuzzy Optim. Decis. Mak, DOI [DOI 10.1023/B:FODM.0000013071.63614.3D, DOI 10.1023/B:FODM.0000013071.63614.3d]
[2]  
Babanli Mustafa, 2021, 11th World Conference Intelligent System for Industrial Automation (WCIS-2020). Advances in Intelligent Systems and Computing (AISC 1323), P254, DOI 10.1007/978-3-030-68004-6_33
[3]   A novel entropy-based weighted attribute selection in enhanced multicriteria decision-making using fuzzy TOPSIS model for hesitant fuzzy rough environment [J].
Dikshit-Ratnaparkhi, Archana ;
Bormane, Dattatraya ;
Ghongade, Rajesh .
COMPLEX & INTELLIGENT SYSTEMS, 2021, 7 (04) :1785-1796
[4]  
Germashev I. V., 2020, Cyber-Physical Systems: Advances in Design & Modelling, Studies in Systems, Decision and Control, V259, DOI [10.1007/978-3-030-32579-4_17, DOI 10.1007/978-3-030-32579-4_17]
[5]   Modelling Compression Strength of Waste PET and SCM Blended Cementitious Grout Using Hybrid of LSSVM Models [J].
Khan, Kaffayatullah ;
Gudainiyan, Jitendra ;
Iqbal, Mudassir ;
Jamal, Arshad ;
Amin, Muhammad Nasir ;
Mohammed, Ibrahim ;
Al-Faiad, Majdi Adel ;
Abu-Arab, Abdullah M. .
MATERIALS, 2022, 15 (15)
[6]   A fuzzy multicriteria decision-making method for material selection [J].
Liao, TW .
JOURNAL OF MANUFACTURING SYSTEMS, 1996, 15 (01) :1-12
[7]   A hybrid fuzzy MCDM approach to machine tool selection [J].
Onut, Semih ;
Kara, Selin Soner ;
Efendigil, Tugba .
JOURNAL OF INTELLIGENT MANUFACTURING, 2008, 19 (04) :443-453
[8]   An integrated fuzzy sustainable supplier evaluation and selection framework for green supply chains in reverse logistics [J].
Tavana, Madjid ;
Shaabani, Akram ;
Santos-Arteaga, Francisco J. ;
Valaei, Naser .
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2021, 28 (38) :53953-53982
[9]   Fuzzy optimization of units products in mix-product selection problem using fuzzy linear programming approach [J].
Vasant, P ;
Barsoum, NN .
SOFT COMPUTING, 2006, 10 (02) :144-151
[10]   Piezoelectric material selection for transducers under fuzzy environment [J].
Vats, Gaurav ;
Vaish, Rahul .
JOURNAL OF ADVANCED CERAMICS, 2013, 2 (02) :141-148