This paper proposes a diversity enhanced multiobjective particle swarm optimization, DEMPSO. Due to the unique velocity each individual has in PSO process, the ...

The region of chaotic search is adaptively adjusted according to the distance between the particle's personal best position and the comprehensive best position.

The experiment results prove the superiority in convergence and diversity. Multiobjective particle swarm optimizations (MOPSOs) are confronted with convergence ...

Dec 19, 2022 · Therefore, balancing convergence and diversity in current MOEAs is difficult. To address these issues, this article proposes a multiobjective ...

N. Al Moubayed, A. Petrovski, J. McCall, A novel smart multi-objective particle swarm optimisation using decomposition, in: Proceedings of the Parallel ...

Jul 24, 2023 · Particle Swarm Optimization (PSO) has received increasing attention from researchers due to its fast convergence ability.

The algorithm evaluates the diversity of the external population in each iteration, and adaptively chooses whether to perform mutation operations on the ...

Particle swarm optimization (PSO) has shown an effective performance for solving variant benchmark and real-world optimization problems.

Dec 10, 2022 · In this paper, an improved MOPSO algorithm based on angle preference called IAPMOPSO is proposed to alleviate those problems. First, to create a ...

Dec 7, 2021 · The current improved MOPSO improves the convergence and diversity of MOPSO to a certain extent, but there are still shortcomings. To further ...