In order to improve performance of particle swarm optimization algorithm (PSO) in global optimization, the reason of premature convergence of the PSO is analyzed, and a new particle swarm optimization based on two subswarms (TSS-PSO) is proposed in this paper. The particle swarm is divided into two identical sub-swarms, that is, the first sub-swarm adopts basic PSO model to evolve, whereas the ...

When a colony of the swarm-founding social wasp Polybia occidentals loses its nest to severe weather or predation, the adult population evacuates and temporarily clusters on nearby foliage. Most of the adults remain inactive in the cluster, while foragers bring in nectar and scout wasps search the surrounding area for a new nesting site. After several hours, the scouts stimulate the rest of the...

Swarm based image analysis is a discipline, in which emphasis is on developing swarms with different rules and interactions for obtaining a specific emergent behavior, which may be used in an image analysis context. As the swarm process and results are readily visible, swarm based image analysis is an excellent discipline for obtaining a greater understanding of swarm theory. Currently there is...

This paper presents a novel and generic distributed swarm guidance algorithm using inhomogeneous Markov chains that guarantees superior performance over existing homogeneous Markov chain based algorithms, when the feedback of the current swarm distribution is available. The probabilistic swarm guidance using inhomogeneous Markov chain (PSG–IMC) algorithm guarantees sharper and faster convergenc...

Reactive power optimization is important to ensure power quality, improve system security, and reduce active power loss. So, this paper proposed parallel immune particle swarm optimization (PIPSO) algorithm. This algorithm makes basic particle swarm optimization (BPSO) and discrete particle swarm optimization (DPSO) to optimize in parallel, and improves the convergence capability of particle sw...

so far various methods for optimization presented and one of most popular of them are optimization algorithms based on swarm intelligence and also one of most successful of them is particle swarm optimization (pso). prior some efforts by applying fuzzy logic for improving defects of pso such as trapping in local optimums and early convergence has been done. moreover to overcome the problem of i...

Swarm robots are special multi-robots and usually considered being controlled with swarm intelligence-basedmethod to complete some assigned complex tasks (Dorigo and Sahin, 2004). Similar to the biological counterparts in nature, swarm intelligence among such artificial system is emerged from local interactions between individual robots or individual robot and its environment (Beni, 2005; Şahin...

This paper presents a dynamic particle swarm optimization based search for optimal fusion configuration of sensors in distributed detection network in presence of a nonstationary binary symmetric channel. The wireless channel in sensor networks is a non-stationary random process, which moves the optima of the original problem, otherwise static. The optimal fusion configuration minimizes the pro...

In modern Peer-to-Peer (P2P) content distribution applications, multiple swarms typically exist, each corresponding to the dissemination of one content among interested peers. A common design in the existing P2P applications is to allow peers in one swarm to help each other, while different swarms are only coupled when sharing the upload bandwidth at the dedicated content servers/publishers. In...

It is a grand challenge to model the emergence of swarm intelligence and many principles or models had been proposed. However, existing models do not catch the nature of swarm intelligence and they are not generic enough to describe various types of emergence phenomena. In this work, we propose a contradiction-centric model for emergence of swarm intelligence, in which individuals’ contradictio...