Abstract— Particle Swarm Optimization (PSO) algorithm is swarm intelligence based algorithm which is used for solving optimization problem. PSO simulates the intelligent foraging behavior of a flock of birds. This paper presents a modification in PSO and develops an algorithm called Highly Convergent Particle Swarm Optimization (HCPSO) algorithm, in which the velocity of particle is made to be ...

Particle swarm optimization (PSO) is a popular and robust strategy for optimization problems. One main difficulty in applying PSO to real-world applications is that PSO usually need a large number of fitness evaluations before a satisfying result can be obtained. This paper introduces a new ”fast particle swarm optimization” (FPSO) that does not evaluate all new positions owning a fitness and a...

A simple and robust methodology is presented to determine the location and amount of crack in beam like structures based on the incremental particle swarm optimization technique. A comparison is made for assessing the performance of standard particle swarm optimization and the incremental particle swarm optimization technique for detecting crack in structural members. The objective function is ...

This paper focus on engineering and computer science aspects of development, applications, and resources related to increase the efficiency of crowd simulation using Particle Swarm Optimization. This paper presents the idea of crowd simulation and uniform conceptual model based on Particle Swarm Optimization paradigm to simulate crowd. Particle Swarm Optimization (PSO) is a technique used to ex...

This paper proposes an effective approach based on binary coding Particle Swarm Optimization (PSO) to identify the switching operation plan for feeder reconfiguration. The proposed method considers the advantages and disadvantages of existing particle swarm optimization method and redefined the operators of PSO algorithm to fit the application field of distribution systems. Shift operator is pr...

This paper develops an efficient and clear insight view about the application of various PSO algorithms to the economic load dispatch problem with emission restrictions as the constraint. Solution acceleration techniques in the algorithm which enhance the speed and robustness of the algorithm are developed. The power and usefulness of the algorithm is demonstrated through its application to a t...

In order to overcome the separately selection advantages of traditional feature and RBF neural network parameter, increase accuracy rate of network’s intrusion detection, there came up with a research on neural network intrusion detection of improved particle swarm optimization. According to optimize the feature selection of network and RBF neural network parameter, established a neural network...

In this paper, a new particle swarm optimization method has been proposed. In the proposed approach a novel philosophy of modifying the velocity update equation of Standard Particle Swarm Optimization approach has been used. The modification has been done by vanishing the gbest term in the velocity update equation of SPSO. The performance of the proposed algorithm (Personal Best Position Partic...

By taking advantage of niche sharing scheme,we propose a novel co-evolutionary particle swarm optimization algorithm (NCPSO) to solve permutation flow shop scheduling problem. As the core of this algorithm, niche sharing scheme maximizes the diversity of population and hence improves the quality of individuals. To evaluate the performance of the proposed algorithm, we have use eight Taillard in...