In this paper, an optimal stable algorithm is presented for members of a robots swarm moving toward a target. Equations of motion of the swarm are based on Lagrangian energy equations. Regarding of similar research On the design of swarm motion algorithm, an equation of motion considered constraints to guarantee no collision between the members and the members and obstacles along the motion pat...

Swarm intelligence is a research branch that models the population of interacting agents or swarms that are able to self-organize. An ant colony, a flock of birds or an immune system is a typical example of a swarm system. Bees’ swarming around their hive is another example of swarm intelligence. Artificial Bee Colony (ABC) Algorithm is an optimization algorithm based on the intelligent behavio...

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...

In optimizing the particle swarm optimization (PSO) that inevitable existence problem of prematurity and the local convergence, this paper base on this aspects is put forward a kind of modified particle swarm optimization algorithm, take the gradient descent method (BP algorithm) as a particle swarm operator embedded in particle swarm algorithm, and at the same time use to attenuation wall (Dam...

Electric power line overhaul plan is an important issue on power system and engineering practice. As particle swarm optimization is to be a new intelligent algorithm. It is gradually applied into power system these years. This paper provides a relative mathematical model to solve the problems in power line overhaul. Particle swarm optimization algorithm has advantages of less parameters setting...

In this article a new algorithm is developed for optimizing computationally expensive simulation models. The optimization algorithm is developed for continues unconstrained single output simulation models. The algorithm is developed using two simulation optimization routines. We employed the nested partitioning (NP) routine for concentrating the search efforts in the regions which are most like...

Artificial Bee colony is one of the most efficient optimizing technique introduced so far. Artificial Bee Colony simulates the brilliant behavior honey bee swarm. Considering the environmental impacts that grow from the emission produced by the conventional fuel power plants, the economic dispatch that minimizes only the total fuel cost can no longer be considered as single objective function. ...

A novel Cooperative Bee Swarm Optimization (CBSO) algorithm based on foraging behaviour of honey bees is presented. The CBSO employs cooperative behaviours of multiple swarms in optimizing numerical functions. The proposed approach provides different patterns which are used by the bees to adjust their flying trajectories. The flying patterns provide an efficient way to balance exploration and e...