Genetic algorithms with sharing for multimodal function optimization
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Archiving With Guaranteed Convergence And Diversity In Multi-objective Optimization
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
An analysis of the behavior of a class of genetic adaptive systems.
An analysis of the behavior of a class of genetic adaptive systems.
The maximin fitness function: multi-objective city and regional planning
EMO'03 Proceedings of the 2nd international conference on Evolutionary multi-criterion optimization
Multi-objective maximin sorting scheme
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
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This work presents a procedure to automate the design of Si-integrated radio frequency (RF) discrete tuning varactors (RFDTVs). The synthesis method, which is based on evolutionary algorithms, searches for optimum performance RF switched capacitor array circuits that fulfill the design restrictions. The design algorithm uses the *** -dominance concept and the maximin sorting scheme to provide a set of different solutions (circuits) well distributed along an optimal front in the parameter space (circuit size and component values). Since all the solutions present the same performance, the designer can select the circuit that is best suited to be implemented in a particular integration technology. To assess the performance of the synthesis procedure, several RFDTV circuits, provided by the algorithm, were designed and simulated using a $0.18\mu\textrm{m}$ CMOS technology and the Cadence Virtuoso Design Platform. The comparisons between the algorithm and circuit simulation results show that they are very close, pointing out that the proposed design procedure is a powerful design tool.