Pareto simulated annealing (SA)-based multi-objective optimization for MEMS design and application

被引:0
|
作者
Ong, AO [1 ]
Tay, FEH [1 ]
机构
[1] Natl Univ Singapore, Dept Mech Engn, Singapore 117576, Singapore
关键词
global optimization; pareto SA; multiple objective functions; MEMS; Pareto ranking;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper we present a global optimization method for multiple objective functions using the Pareto Simulated Annealing (SA). This novel optimization method is very useful and promising for design and application in the field of Micro-Electro-Mechanical Systems (MEMS), Previously published global optimization method has been reported by us for only single objective function. The proposed method automatically assigns different objective weights to each objective functions so that it can generate multiple solutions simultaneously. It also offers the trade-off between the objective functions so that we will be able to select the most suitable solution for MEMS design and applications. Based on the global Pareto ranking of the solutions, the optimization method can provide the best solution (the first Pareto ranking) as well.
引用
收藏
页码:455 / 460
页数:6
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