Particle Swarm Optimization

Hybrid global/local derivative-free multi-objective optimization via deterministic particle swarm with local linesearch

A multi-objective deterministic hybrid algorithm (MODHA) is introduced for efficient simulation-based design optimization. The global exploration capability of multi-objective deterministic particle swarm optimization (MODPSO) is combined with the local search accuracy of a derivative-free multi-objective (DFMO) linesearch method. Six MODHA formulations are discussed, based on two MODPSO formulations and three DFMO activation criteria. Forty five analytical test problems are solved, with two/three objectives and one to twelve variables.

Electromagnetic characterization of advanced nanostructured materials and multilayer design optimization for metrological and low radar observability applications

In this work the electromagnetic characterization of composite materials reinforced with carbon and metallic nanoparticles is presented. In particular, the electric permittivity and the magnetic permeability as a function of the frequency are used to evaluate the electromagnetic absorption capability of the nanocomposites. The aim is the study of possible applications in advanced coating able to tune the electromagnetic reflectivity of satellite surfaces in specific frequency ranges, in a special way for those surfaces that for some reason could be exposed to the antenna radiation pattern.

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