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A multi-objective optimization method for uncertain structures based on nonlinear interval number programming method

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成果类型:
期刊论文
作者:
Liu, Xin;Zhang, Zhiyong*;Yin, Lairong
通讯作者:
Zhang, Zhiyong
作者机构:
[Liu, Xin; Yin, Lairong; Zhang, Zhiyong] Changsha Univ Sci & Technol, Educ Dept Hunan Prov, Key Lab Lightweight & Reliabil Technol Engn Vehic, Wang Jia Li South Rd 960, Changsha 410004, Hunan, Peoples R China.
[Liu, Xin] Xi An Jiao Tong Univ, State Key Lab Strength & Vibrat Mech Struct, Xian, Shanxi, Peoples R China.
通讯机构:
[Zhang, Zhiyong] C
Changsha Univ Sci & Technol, Educ Dept Hunan Prov, Key Lab Lightweight & Reliabil Technol Engn Vehic, Wang Jia Li South Rd 960, Changsha 410004, Hunan, Peoples R China.
语种:
英文
关键词:
Constrained optimization;Genetic algorithms;Numerical methods;Optimization;Pareto principle;Constraint optimization problems;Intergeneration-projection genetic algorithms;Interval number programming;Micro multi-objective genetic algorithm;Pareto-optimal sets;Penalty function methods;Single objective optimization problems;Uncertainty structure;Multiobjective optimization
期刊:
Mechanics Based Design of Structures and Machines
ISSN:
1539-7734
年:
2017
卷:
45
期:
1
页码:
25-42
基金类别:
National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [51305047]; Specialized Research Fund for the Doctoral Program of Higher EducationSpecialized Research Fund for the Doctoral Program of Higher Education (SRFDP) [20134316120003]; Science Foundation of State Key Laboratory for Strength and Vibration of Mechanical Structures [SV2016-KF-09]; Science Fund of the Key Laboratory of Lightweight and Reliability Technology for Engineering Vehicle, Education Department of Hunan Province [2014KFJJ06]
机构署名:
本校为第一且通讯机构
院系归属:
汽车与机械工程学院
摘要:
A multi-objective optimization method for uncertain structures is developed based on nonlinear interval number programming (NINP) method. The NINP method is employed to transform each uncertain objective function into a deterministic single-objective optimization problem. Using the constraint penalty function method, a deterministic multi-objective and non-constraint optimization problem is formulated in terms of penalty functions. Then the micro multi-objective genetic algorithm and the intergeneration projection genetic algorithm are adopted ...

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