Open AccessJournal Article
Multiobjective Optimization
Sai Ho Yeung,Kim Fung Man +1 more
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TLDR
In this paper, a wireless communication system consists of various passive components, including antennas, directional couplers, phase shifters, and filters, and the mathematical approach may use some assumptions in the calculation that introduces differences between the calculated dimensions and the actual dimensions.Abstract:
A wireless communication system consists of various passive components, including antennas, directional couplers, phase shifters, and filters. These components have many dimensional parameters that must be determined. For instance, a coupled line section has line width, gap between the coupled lines, and the length of the line as the parameters to be determined. Identifying these parameters through trial and error is ineffective. Meanwhile, the mathematical approach may be very complex and may use some assumptions in the calculation that introduces differences between the calculated dimensions and the actual dimensions.read more
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References
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An efficient method for finding the minimum of a function of several variables without calculating derivatives
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Evolutionary Algorithms for Multiobjective Optimization: Methods and Applications
TL;DR: The basic principles of evolutionary multiobjective optimization are discussed from an algorithm design perspective and the focus is on the major issues such as fitness assignment, diversity preservation, and elitism in general rather than on particular algorithms.