A comprehensive learning particle swarm optimizer (CLPSO) embedded with local search
(LS) is proposed to pursue higher optimization performance by taking the advantages of …

There exist many multiobjective optimization problems (MOPs) containing a large number of
decision variables in real-world applications, which are known as large-scale MOPs. Due to …

While the industrial Internet of Things (IIoT) can support efficient control of the physical world
through large amounts of industrial data, data security has been a challenge due to various …

As a powerful optimization technique, multi-objective particle swarm optimization algorithms
have been widely used in various fields. However, performing well in terms of convergence …

Dear editor, Swarm intelligence optimization algorithms are inspired by the behaviour of
biological groups in nature. Such algorithms have the advantages of a clear structure …

The key aspect in coal production is realizing safe and efficient mining to maximize the
utilization of the resources. A requirement for sustainable economic development is realizing …

The application of multiobjective evolutionary algorithms to many-objective optimization
problems often faces challenges in terms of diversity and convergence. On the one hand …

Feature selection is a multi-objective optimization problem since it has two conflicting
objectives: maximizing the classification accuracy and minimizing the number of the …

With accelerated ensemble of the Internet of Things technology and automotive industry,
vehicular network has been established as powerful tools. However, it is a significant …

Rail vehicles offer the characteristics of large carrying capacity and high running speed.
Train accidents usually result in substantial personal casualties and economic losses …