IEEE Transactions on Magnetics · 2005 · 129 citations · 7 references
ArchitectureComputational EngineeringElectrical EngineeringComputational ElectromagneticsDesign OptimizationOptimizationCombinatorial OptimizationEvolutionary ComputationEvolutionary OptimizationGenetic AlgorithmsParameter OptimizationPopulation-based SearchElectromagnetic DesignEvolutionary AlgorithmsGenetic Algorithm Based DesignGenetic Algorithm OptimizationGenetic Algorithms For DesignMutationPopulation Based Design OptimizationPopulation-based Optimization
This paper proposes the real-coded clonal selection algorithm (RCSA) for use in electromagnetic design optimization. Some features of the algorithm, such as the number of clones, mutation range, and the fraction of the population selected each generation are discussed. The TEAM Workshop problem 22 is investigated, in order to illustrate the performance of the algorithm in a real electromagnetic problem. The results obtained, a set of optimal solutions representing a broader range of options for the designer, are compared with those achieved by a genetic algorithm, showing the efficiency of the RCSA in practical optimization problems.
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