This article proposes a novel and computationally efficient explicit intertask information
transfer strategy between optimization tasks by aligning the subspaces. In evolutionary …

An immunity enhanced particle swarm optimization (IEPSO) algorithm, which combines
particle swarm optimization (PSO) with the artificial immune system, is proposed for damage …

The learning strategy in the canonical particle swarm optimization (PSO) algorithm is often
blamed for being the primary reason for loss of diversity. Population diversity maintenance is …

Global optimization remains one of the most challenging tasks for evolutionary computation
and swarm intelligence. In recent years, there have been some significant developments in …

An approach based on an improved particle swarm optimization (PSO) algorithm is
proposed for structural damage detection in this study. A disturbance is introduced in the …

In recent years, particle swarm optimization (PSO) has extensively applied in various
optimization problems because of its simple structure. Although the PSO may find local …

摘要该文提出一种基于非均匀变异和多阶段扰动的粒子群优化算法, 并对算法的搜索性能进行了
一般性分析. 首先, 在算法执行的不同阶段利用对当前最优解施加大小不同的邻域扰动操作 …

Existing multifactorial particle swarm optimization algorithms treat all particles equally with a
consistent inter-task exemplar selection and generation strategy. This may lead to poor …

Existing multifactorial particle swarm optimisation (MFPSO) algorithms only explore a
relatively narrow area between the inter‐task particles. Meanwhile, these algorithms use a …

The control and estimation of unknown parameters of chaotic systems are a daunting task till
date from the perspective of nonlinear science. Inspired from ecological co-habitation, we …