Many-Objective Optimisation of Trusses Through Meta-Heuristics

被引:10
作者
Pholdee, Nantiwat [1 ]
Bureerat, Sujin [1 ]
Jaroenapibal, Papot [2 ]
Radpukdee, Thana [1 ]
机构
[1] Khon Kaen Univ, Dept Mech Engn, Fac Engn, Aircraft Multidisciplinary Optimisat Res Unit, Khon Kaen 40002, Thailand
[2] Khon Kaen Univ, Dept Ind Engn, Fac Engn, Khon Kaen 40002, Thailand
来源
ADVANCES IN NEURAL NETWORKS, PT I | 2017年 / 10261卷
关键词
Many-objective optimisation; Truss design; Meta-heuristics; Evolutionary computation; Constrained optimisation; ALGORITHM; SIZE;
D O I
10.1007/978-3-319-59072-1_18
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A truss is one of the most used engineering structures in daily life due to several advantages. A process for truss optimisation is usually set to minimise its mass while structural safety constraints are imposed. This design problem always leads to structures with less reliability since the solution is generally on the borderline of structural failure. Such a phenomenon can be alleviated by adding effects of all possible load cases with safety factors to design constraints. Alternatively, the design problem should be many-objective optimisation assigned to optimise mass and reliability indicators for all load cases. This paper is the first attempt to study such a design process. A number of many-objective meta-heuristics are employed to solve the test problems for many-objective truss optimization where their performances are compared.
引用
收藏
页码:143 / 152
页数:10
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