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 …

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

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 …

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

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 …

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 …

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

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 …

With the advantages of easy deployment and flexible usage, unmanned aerial vehicle (UAV)
has advanced the multitarget tracking (MTT) applications. The UAV-MTT system has great …

Handling conflicting objectives and finding multiple Pareto optimal solutions are two
challenging issues in solving multiobjective optimization problems (MOPs). Inspired by the …