Please use this identifier to cite or link to this item: https://doi.org/10.1142/S021819400500221X
Title: Pareto Simulated Annealing (SA)-based multi-objective optimization for mems design and application
Authors: Ong, A.O. 
Tay, F.E.H. 
Keywords: Global optimization
MEMS
Multiple objective functions
Pareto ranking
Pareto SA
Issue Date: Apr-2005
Source: Ong, A.O.,Tay, F.E.H. (2005-04). Pareto Simulated Annealing (SA)-based multi-objective optimization for mems design and application. International Journal of Software Engineering and Knowledge Engineering 15 (2) : 455-460. ScholarBank@NUS Repository. https://doi.org/10.1142/S021819400500221X
Abstract: 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 Parcto ranking of the solutions, the optimization method can provide the best solution (the first Pareto ranking) as well. © World Scientific Publishing Company.
Source Title: International Journal of Software Engineering and Knowledge Engineering
URI: http://scholarbank.nus.edu.sg/handle/10635/61047
ISSN: 02181940
DOI: 10.1142/S021819400500221X
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