N Zeng, Z Wang, W Liu, H Zhang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
In this article, a dynamic-neighborhood-based switching PSO (DNSPSO) algorithm is proposed, where a new velocity updating mechanism is designed to adjust the personal …
R Cheng, Y Jin - IEEE transactions on cybernetics, 2014 - ieeexplore.ieee.org
In this paper, a novel competitive swarm optimizer (CSO) for large scale optimization is proposed. The algorithm is fundamentally inspired by the particle swarm optimization but is …
R Cheng, Y Jin - Information Sciences, 2015 - Elsevier
Social learning plays an important role in behavior learning among social animals. In contrast to individual (asocial) learning, social learning has the advantage of allowing …
Particle swarm optimizer is a well-known efficient population and control parameter-based algorithm for global optimization of different problems. This paper focuses on a new and …
An important consideration of multiobjective optimization (MOO) is the quantitative metrics used for defining the optimality of different solution sets, which is also the basic principle for …
M Gong, Q Cai, X Chen, L Ma - IEEE Transactions on …, 2013 - ieeexplore.ieee.org
The field of complex network clustering has been very active in the past several years. In this paper, a discrete framework of the particle swarm optimization algorithm is proposed. Based …
Y Ma, M Hu, X Yan - ISA transactions, 2018 - Elsevier
This paper investigates the path planning problem for unmanned surface vehicle (USV), wherein the goal is to find the shortest, smoothest, most economical and safest path in the …
Evolutionary multiobjective optimization has been a research area since the mid-1980s, and has experienced a very significant activity in the last 20 years. However, and in spite of the …
Multimodal optimization amounts to finding multiple global and local optima (as opposed to a single solution) of a function, so that the user can have a better knowledge about different …