We dramatically improve convergence speed and global exploration capabilities of particle swarm optimization (PSO) through a targeted position-mutated elitism (PSO-TPME). The three key innovations address particle classification, elitism, and mutation in the cognitive and social model. PSO-TPME is benchmarked against five popular PSO variants for multi-dimensional functions, which are extensively adopted in the optimization field, In particular, the convergence accuracy, convergence speed, and the capability to find global minima is investigated. The statistical error is assessed by numerous repetitions. The simulations demonstrate that proposed PSO variant outperforms the other variants in terms of convergence rate and accuracy by orders of magnitude.
翻译:通过有针对性的定位精英(PSO-TPME),我们大大提高了粒子群优化(PSO)的趋同速度和全球探索能力,这三项关键创新涉及粒子分类、精英化以及认知和社会模式的突变。PSO-TPME参照了在优化领域广泛采用的五种多维功能流行的PSO变体,特别是趋同精确度、趋同速度和找到全球迷你的能力。通过多次重复对统计错误进行了评估。模拟表明,拟议的PSO变体在趋同率和数量级准确性方面优于其他变体。