This paper attempts to bring forward various newly emerged natural computing techniques to a common platform. Six such techniques are compared among each other which have been used to solve a w ell known classical problem, the travelling salesman problem. The techniques discussed in this paper are Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Bacterial Foraging Optimization ...

According to the intelligent behavior of social population, the centroid of the individual best of particle swarm is firstly introduced in particle swarm optimization (PSO) model to enhance inter-particle cooperation and information sharing capabilities, then combining the mechanism of population migration algorithm (PMA), a novel PSO algorithm with adaptive space mutation (PMCPSO) is proposed ...

in this paper, we proposed an algorithm for solving the problem of task scheduling using particle swarm optimization algorithm, with changes in the selection and removing the guide and also using the technique to get away from the bad, to move away from local extreme and diversity. scheduling algorithms play an important role in grid computing, parallel tasks scheduling and sending them to appr...

Swarm robotics is a new area of interest that’s inspired from biological system of ants, birds and other social systems for solving different optimization problem. This paper work out to find the optimal path using particle swarm optimization algorithm and dijkstra’s algorithm, these algorithms are used to find the shortest path between different nodes. Different path can exist from one node to...

Estimation of the boundary condition is a critical problem in simulating hemodynamics in microvascular networks. This paper proposed a boundary estimation strategy based on a particle swarm optimization (PSO) algorithm, which aims to minimize the number of vessels with inverted flow direction in comparison to the experimental observation. The algorithm took boundary values as the particle swarm...

This paper presents a newly developed approach to find the optimal location of distributed generations (DGs) to improve power system voltage stability margin and reduce losses incorporating the constraints. The loadability limit index is used to assess the static voltage stability security margin, which is associated with the point of voltage collapse limit. Based on this, a toolbox is develope...

Wind Power forecasting is an important subject of concern for reliable operations of grid and it has been studied from different points of views of both accuracy and reliability. So with an aim of improvement in prediction accuracy this paper presents a hybrid wind power prediction machine for Ontario Electricity Market (OEM) on single step ahead basis in which Wavelet Transform (WT) is used fo...

Standard particle swarm optimization is easy to fall into local optimum and has the problem of low precision. To solve these problems, the paper proposes an effective approach, called particle swarm optimization based on multiple swarms and opposition-based learning, which divides swarm into two subswarms. The 1st sub-swarm employs PSO evolution model in order to hold the self-learning ability;...

This paper introduces collaborating robots which provide the possibility of enhanced task performance, high reliability and decreased. Collaborating-bots are a collection of mobile robots able to self-assemble and to self-organize in order to solve problems that cannot be solved by a single robot. These robots combine the power of swarm intelligence with the flexibility of self-reconfiguration ...

This paper shows the results obtained in the analysis of the impact of distributed generation (DG) on distribution losses and presents a new algorithm to the optimal allocation of distributed generation resources in distribution networks. The optimization is based on a Hybrid Genetic Algorithm and Particle Swarm Optimization (HGAPSO) aiming to optimal DG allocation in distribution network. Thro...