Many areas in power systems require solving one or more nonlinear optimization problems. Particle swarm optimization (PSO), part of the swarm intelligence family, is known to effectively solve large-scale nonlinear optimization problems. This paper presents a detailed overview of the basic concepts of PSO and its variants. The proposed method utilizes the Particle Swarm Optimization (PSO) algor...

This paper introduced a new swarm based optimization technique for tuning Power System Stabilizer (PSS) that attached to a synchronous generator in a single machine infinite bus (SMIB) system. PSS which is installed with Lead-Lag (LL) controller is introduced to elevate the damping capability of the generator in the low frequency mode. For tuning PSS-LL parameters, a new technique called Whale ...

Two important topics in Particle Swarm Optimization (PSO) research filed are trajectory analysis of particles and parameter selection method. Trajectory analysis is important because it can help to determine where the position of each particle is at each evolutionary step, and consequently it can help to clarify the running mechanism of PSO algorithm, so as to explain why and when PSO algorithm...

Engineering optimization problems usually have several conflicting objectives, such that no single solution can be considered optimum with respect to all objectives. In recent years, many efforts have focused on hybrid metaheuristic approaches for their robustness and efficiency to solve the above-mentioned multiobjective optimization problems (MOPs). This paper proposes a novel hybrid algorith...

Multilevel thresholding is one of the most popular image segmentation techniques. This paper presents a new multilevel maximum entropy thresholding method based on modified seeker optimization (MSO) algorithm. In the proposed method the thresholding problem is treated as an optimization problem and solved by using the MSO metaheuristics. Particle swarm optimization (PSO) algorithm is also imple...

this paper presents a relatively new management model for the optimal design and operation of irrigation water pumping systems. the model makes use of the newly introduced particle swarm optimization algorithm. a two step optimization model is developed and solved with the particle swarm optimization method. the model first carries out an exhaustive enumeration search for all feasible sets of p...

The increased nature of email spam with the use of urge mailing tools prompt the need for detector generation to counter the menace of unsolocited email. Detector generation inspired by the human immune system implements particle swarm optimization (PSO) to generate detector in negative selection algorithm (NSA). Outlier detectors are unique features generated by local outlier factor (LOF). The...

In this work, we suggest that the poorer results obtained with particle swarm optimization (PSO) in some previous studies should be attributed to the cross-validation scheme commonly employed to improve generalization of PSO-trained neural network river forecasting (NNRF) models. Crossvalidation entails splitting the training dataset into two, and accepting particle position updates only if fit...

This paper presented a new particle swarm optimization based on evolutionary game theory (EPSO) for the traveling salesman problem (TSP) to overcome the disadvantages of premature convergence and stagnation phenomenon of traditional particle swarm optimization algorithm (PSO). In addition ,we make a mapping among the three parts discrete particle swarm optimization (DPSO)、 evolutionary game the...