A comprehensive survey on particle swarm optimization algorithm and its applications
Particle swarm optimization (PSO) is a heuristic global optimization method, proposed
originally by Kennedy and Eberhart in 1995. It is now one of the most commonly used …
originally by Kennedy and Eberhart in 1995. It is now one of the most commonly used …
Phasor particle swarm optimization: a simple and efficient variant of PSO
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 …
algorithm for global optimization of different problems. This paper focuses on a new and …
A survey of algorithms, applications and trends for particle swarm optimization
Particle swarm optimization (PSO) is a popular heuristic method, which is capable of
effectively dealing with various optimization problems. A detailed overview of the original …
effectively dealing with various optimization problems. A detailed overview of the original …
Particle swarm optimization
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A unified algorithm based on HTS and self-adapting PSO for the construction of octagonal and rectilinear SMT
The Steiner minimal tree (SMT) problem is an NP-hard problem, which is the best
connection model for a multi-terminal net in global routing problem. This paper presents a …
connection model for a multi-terminal net in global routing problem. This paper presents a …
An adaptive particle swarm optimization method based on clustering
Particle swarm optimization (PSO) is an effective method for solving a wide range of
problems. However, the most existing PSO algorithms easily trap into local optima when …
problems. However, the most existing PSO algorithms easily trap into local optima when …
A PSO-based timing-driven Octilinear Steiner tree algorithm for VLSI routing considering bend reduction
G Liu, W Guo, Y Niu, G Chen, X Huang - Soft Computing, 2015 - Springer
Constructing a timing-driven Steiner tree is very important in VLSI performance-driven
routing stage. Meanwhile, non-Manhattan architecture is supported by several …
routing stage. Meanwhile, non-Manhattan architecture is supported by several …
Performance analysis of synchronous and asynchronous distributed genetic algorithms on multiprocessors
Because of their effectiveness and flexibility in finding useful solutions, Genetic Algorithms
(GAs) are very popular search techniques for solving complex optimization problems in …
(GAs) are very popular search techniques for solving complex optimization problems in …
Feature selection and classifier parameters estimation for EEG signals peak detection using particle swarm optimization
Electroencephalogram (EEG) signal peak detection is widely used in clinical applications.
The peak point can be detected using several approaches, including time, frequency, time …
The peak point can be detected using several approaches, including time, frequency, time …
Improving particle swarm optimization via adaptive switching asynchronous–synchronous update
Particle swarm optimization (PSO) is a population-based metaheuristic optimization
algorithm that solves a problem through iterative operations. Traditional PSO iteration …
algorithm that solves a problem through iterative operations. Traditional PSO iteration …