Diversity control in the particle swarm optimization (PSO) algorithm is one of the important issues that influence the process of finding global optimal solution. In this study we create a historical process to find best area of the search space for population dispersion guide on PSO algorithm, and name Diversity Guided Particle Swarm Optimization algorithm (DGPSO) algorithm. Hence we propose a...

This paper presents an algorithm of particle swarm optimization with reduction for global optimization problems. Particle swarm optimization is an algorithm which refers to the collective motion such as birds or fishes, and a multi-point search algorithm which finds a best solution using multiple particles. Particle swarm optimization is so flexible that it can adapt to a number of optimization...

In recent days, Swarm Intelligence plays an important role in solving many real life optimization problems. Particle Swarm Optimization (PSO) is swarm intelligence based search and optimization algorithm which is used to solve global optimization problems. But due to lack of population diversity and premature convergence it is often trapped into local optima. We can increase diversity and preve...

Sinter tumbler strength is an important parameter in the sintering process, and has an important influence on the performance of finished sinter. Artificial fish swarm algorithm have good ability to acquire the global performance, the neural network has strong nonlinear ability and local optimization performance,; AFSA+BP algorithm combined with artificial fish swarm algorithm and BP algorithm,...

Sinter tumbler strength is an important parameter in the sintering process, and has an important influence on the performance of finished sinter. Artificial fish swarm algorithm have good ability to acquire the global performance, the neural network has strong nonlinear ability and local optimization performance,; AFSA+BP algorithm combined with artificial fish swarm algorithm and BP algorithm,...

nowadays, economic load dispatch between generation units with least cost involved is one of the most important issues in utilizing power systems. in this paper, a new method i.e. water cycle algorithm (wca) which is similar to other intelligent algorithm and is based on swarm, is employed in order to solve the economic load dispatch problem between power plants. wca is used to solve complicate...

This paper presents a hybrid particle swarm algorithm for solving the multiobjective reactive power dispatch problem. Modal analysis of the system is used for static voltage stability assessment. Loss minimization and maximization of voltage stability margin are taken as the objectives. Generator terminal voltages, reactive power generation of the capacitor banks and tap changing transformer se...

In this paper, a well known NP-hard problem, the Constrained Shortest Path problem, is studied. As efficient metaheuristic approaches are required for its solution, a new hybridized version of Particle Swarm Optimization algorithm with Variable Neighborhood Search is proposed for solving this significant combinatorial optimization problem. Particle Swarm Optimization (PSO) is a population-based...

The Robotic Darwinian Particle Swarm Optimization (RDPSO) previously proposed is an evolutionary algorithm that benefits from a natural selection mechanism designed to solve complex tasks (e.g., search and rescue). Yet, the stochasticity inherent to this algorithm makes it hard to predict teams’ performance under specific situations and, therefore, almost impossible to synthesize the most right...