Accelerating particle swarm optimization using crisscross search
This paper introduces a novel crisscross search particle swarm optimizer called CSPSO. The CSPSO algorithm has significant superiority over most of the other PSO variants in terms of solution accuracy and convergence rate. The swarm in CSPSO is directly represented by a population of pbests, which are renewed by the modified PSO search as well as the crisscross search in sequence at each generation. The CSO as an catalytic agent can accelerate the particles to converge to the global optima. The horizontal crossover uses a cross-border search mechanism to enhance the global search ability greatly. The vertical crossover can facilitate the stagnant dimensions to escape out of the local minima.
horizontal crossover global search vertical crossover particle swarm optimization (pso) crisscross search optimization (cso)