Sabine Helwig

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— When applying Particle Swarm Optimization (PSO) to real world optimization problems, often boundary constraints have to be taken into account. In this paper, we will show that the bound handling mechanism essentially influences the swarm behavior, especially in high-dimensional search spaces. In our theoretical analysis, we will prove that all particles(More)
—Many practical optimization problems are constrained , and have a bounded search space. In this paper, we propose and compare a wide variety of bound handling techniques for particle swarm optimization. By examining their performance on flat landscapes, we show that many bound handling techniques introduce a significant search bias. Furthermore, we compare(More)
The interaction among particles is a vital aspect of Particle Swarm Optimization. As such, it has a strong influence on the swarm's success. In this study various approaches regarding the particles' communication behavior and their relationship are examined, as well as possibilities to combine the approaches. A new variant of the popular FIPS algorithm, the(More)
Particle swarm optimization (PSO) is a nature-inspired technique originally designed for solving continuous optimization problems. There already exist several approaches that use PSO also as basis for solving discrete optimization problems, in particular the Traveling Sales-person Problem (TSP). In this paper, (i) we present the first theoretical analysis(More)
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