less than 1 minute read

Particle Swarm Optimization (PSO) is a method for numerical optimization. Here, the candidate solutions are represented by particles flying through ${\mathbb{R}}^n$, each having a velocity vector. The velocities of the particles are influenced by neighboring particles and by the objective function via best-so-far positions.

Posts

Why research in Computational Intelligence should be less nature-inspired.

17 minute read

The inspiration gleaned from observing nature has led to several important advances in the field of optimization. Still, it seems to me that a lot of work is mainly based on such inspiration alone. This might divert attention away from practical and algorithmic concerns. As a result, there is a growing number of specialized terminologies used in the field of Evolutionary Computation () and Swarm Intelligence (), which I consider as a problem for clarity in research. With this article, I would like to formulate my thoughts with the hope to contribute to a fruitful debate.

Publications

  • Yu WANG, Bin LI (李斌), Thomas Weise (汤卫思), Jianyu WANG, Bo YUAN (袁博), and Qiongjie TIAN: Self-Adaptive Learning Based Particle Swarm Optimization. Information Sciences 181(20):4515-4538. October 2011.