Critical Comparison of Multi-objective Optimization Methods: Genetic Algorithms versus Swarm Intelligence
Alternative metrics PlumXhttp://hdl.handle.net/11012/57006
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The paper deals with efficiency comparison of two global evolutionary optimization methods implemented in MATLAB. Attention is turned to an elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) and a novel multi-objective Particle Swarm Optimization (PSO). The performance of optimizers is compared on three different test functions and on a cavity resonator synthesis. The microwave resonator is modeled using the Finite Element Method (FEM). The hit rate and the quality of the Pareto front distribution are classified.
Document typePeer reviewed
SourceRadioengineering. 2010, vol. 19, č. 3, s. 369-377. ISSN 1210-2512
- 2010/3