Swarm intelligence is the discipline that deals with natural and artificial systems composed of many individuals that coordinate using decentralized control and self-organization. In particular, the discipline focuses on the collective behaviors that result from the local interactions of the individuals with each other and with their environment. Examples of systems studied by swarm intelligenc...

Artificial Bee Colony (ABC) algorithm is one of the most recently introduced swarm-based algorithms. ABC simulates the intelligent foraging behaviour of a honeybee swarm. In this work, ABC is used for optimizing a large set of numerical test functions and the results produced by ABC algorithm are compared with the results obtained by genetic algorithm, particle swarm optimization algorithm, dif...

Swarm intelligence forms the core of a new class of algorithms inspired by the social behavior of insects that live in swarms. Its attractive features include adaptation, robustness and a distributed, decentralized nature, rendering swarm-based algorithms well-suited for routing in wireless or satellite networks, where it is difficult it implement centralized network control. We propose one suc...

Collective robotics offers the promise of enhanced performance and robustness relative to that of individual robots, with decreased cost or time-to-completion for certain tasks. Having many degrees of freedom, the multi-robot control and estimation problems are challenging, specifically when the solutions require a great amount of communication among the robots. While numerical simulation is a ...

Internet of Things is the extension and expansion of Internet from the virtual world to the real world, in which a large number of resource-constrained devices are used to collaborative perception, and it identifies objects and gathers information in the case of no centralized control, no global model. However, the swarm intelligence can take advantage of many simple autonomous individuals to e...

A weapon system consisting of a swarm of air vehicles whose mission is to search for, classify, attack, and perform battle damage assessment, is considered. It is assumed that the target field information is communicated to all the elements of the swarm as it becomes available. A network flow optimization problem is posed whose readily obtained solution yields the optimum resource allocation am...

This paper describes a Swarm Granulator, a new application of particle swarms to sound synthesis. Granulation, an established technique in sound synthesis, depends on many parameters which are non-intuitive and hard to control from a human perspective. It is proposed here that a particle swarm can organize these parameters and produce musically interesting and novel timbres. A crucial element o...

PSO algorithm is an intelligent optimization algorithm based on swarm intelligence. Particle swarm optimization algorithm is simple, easy to implement, and it has a wide application prospect in scientific research and engineering applications. In real life, most of the optimization problem is the optimization problem of some nonlinear discrete with the existence of local. PSO algorithm also has...

Swarm Intelligence in the form of Particle Swarm Optimization (PSO) has potential applications in electric drives. The excellent characteristics of PSO may be successfully used to optimize the performance of electric machines and electric drives in many aspects. It is estimated that, electric machines consume more than 50% of the world electric energy generated. Improving efficiency in electric...