Network reliability evaluation for fuzzy components: An interval programming approach

被引：5

作者：

Mahapatra, G. S. ^{[1
]}

Mahapatra, B. S. ^{[2
]}

Roy, P. K. ^{[3
]}

机构：

[1] Natl Inst Technol Puducherry, Dept Math, Karaikal 609605, India

[2] Seacom Engn Coll, Dept Math, Sankrail, Howrah, India

[3] Jadavpur Univ, Dept Math, Kolkata, W Bengal, India

来源：

JOURNAL OF INTELLIGENT & FUZZY SYSTEMS | 2014年 / 27卷 / 02期

关键词：

Interval nonlinear programming; fuzzy set; network system; reliability; trapezoidal fuzzy number; NUMBER ARITHMETIC OPERATIONS; SYSTEM RELIABILITY; UNCERTAIN OPTIMIZATION; MODEL;

D O I：

10.3233/IFS-131032

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The probabilistic reliability estimation of complex system is complicated due to uncertainty of failure data, modeling or human failure. In this paper, reliability of components of complex network system is considered as fuzzy in nature to reduce the uncertainty. Trapezoidal fuzzy number is used to represent component's reliability of network system. Then the reliability of the network system is assembled with fuzzy reliability of components and evaluated by Zadeh's extension principle. Fuzzy reliability of the network system becomes an interval by alpha-cuts operation. Interval nonlinear programming is used to evaluate the optimum network's system reliability with interval valued cost constraint. The above approach is explained in details through a numerical example of very useful power system network of electrical engineering.

引用

页码：743 / 751

页数：9

共 50 条

[21] Reliability-network-equivalent approach to distribution-system-reliability evaluation [J].

Billinton, R ;

Wang, P .

IEE PROCEEDINGS-GENERATION TRANSMISSION AND DISTRIBUTION, 1998, 145 (02) :149-153

[22] A fuzzy multiobjective linear programming approach for green multiechelon distribution network design [J].

Tai, Pham Duc ;

Jinawat, Krit ;

Buddhakulsomsiri, Jirachai .

JOURNAL OF MODELLING IN MANAGEMENT, 2024, 19 (03) :1024-1055

[23] Fuzzy System Reliability Analysis Based on Confidence Interval [J].

Jamkhaneh, Ezzatallah Baloui ;

Nozari, Azam .

MATERIALS SCIENCE AND INFORMATION TECHNOLOGY, PTS 1-8, 2012, 433-440 :4908-+

[24] Fuzzy mathematical programming approach to heterogeneous multiattribute decision-making with interval-valued intuitionistic fuzzy truth degrees [J].

Wan, Shu-Ping ;

Li, Deng-Feng .

INFORMATION SCIENCES, 2015, 325 :484-503

[25] A Fuzzy Goal Programming Approach for Solving Multiobjective Fuzzy Stochastic Programming Problems [J].

Pal, Bijay Baran ;

Sen, Shyamal ;

Kumar, Mousumi .

2009 INTERNATIONAL CONFERENCE ON INDUSTRIAL AND INFORMATION SYSTEMS, 2009, :239-+

[26] Fuzzy goal programming approach to multilevel programming problems [J].

Pramanik, Surapati ;

Roy, Tapan Kumar .

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2007, 176 (02) :1151-1166

[27] A Fuzzy Approach to Support Evaluation of Fuzzy Cross Efficiency [J].

Wu, Shun-Cheng ;

Lu, Tim ;

Liu, Shiang-Tai .

SYMMETRY-BASEL, 2021, 13 (05)

[28] A new approach for analysing the fuzzy system reliability using intuitionistic fuzzy number [J].

Kumar M. ;

Yadav S.P. ;

Kumar S. .

International Journal of Industrial and Systems Engineering, 2011, 8 (02) :135-156

[29] A new fuzzy approach based on BWM and fuzzy preference programming for hospital performance evaluation: A case study [J].

Amiri, Maghsoud ;

Hashemi-Tabatabaei, Mohammad ;

Ghahremanloo, Mohammad ;

Keshavarz-Ghorabaee, Mehdi ;

Zavadskas, Edmundas Kazimieras ;

Antucheviciene, Jurgita .

APPLIED SOFT COMPUTING, 2020, 92

[30] Goal programming approaches to deriving interval weights based on interval fuzzy preference relations [J].

Wang, Zhou-Jing ;

Li, Kevin W. .

INFORMATION SCIENCES, 2012, 193 :180-198

← 1 2 3 4 5 →