In this work, we propose a Hybrid particle swarm optimization-Simulated annealing algorithm and present a comparison with i) Simulated annealing algorithm and ii) Back propagation algorithm for training neural networks. These neural networks were then tested on a classification task. In particle swarm optimization behaviour of a particle is influenced by the experiential knowledge of the partic...

Blind source separation technique separates mixed signals blindly without any information on the mixing system. In this paper, we have used two evolutionary algorithms, namely, genetic algorithm and particle swarm optimization for blind source separation. In these techniques a novel fitness function that is based on the mutual information and high order statistics is proposed. In order to evalu...

The appropriate output of distributed generation (DG) in a distribution network is important for maximizing the benefit of the DG installation in the network. Therefore, most researchers have concentrated on the optimization technique to compute the optimal DG value. In this paper, the comparative learning in global particle swarm optimization (CLGPSO) method is introduced. The implementation o...

cellular manufacturing system is one of the most important applications of group technology. design of this system involves many structural and operational issues, in which the cell formation and production planning are two important steps. in this paper, a new mathematical model is proposed for integration of cell formation and production planning problems with the aim of minimizing the overal...

the paper studies optimization of shell-and-tube heat exchangers using the particle swarm optimization technique. a total cost function is formulated based on initial and annual operating costs of the heat exchangers. six variables – shell inside diameter, tube diameter, baffle spacing, baffle cut, number of tube passes and tube layouts (triangular or square) – are considered as the design para...

Cloud Computing is subscription-based service which is used to obtain storage space on network and computer resources. The cloud makes it possible to access information from anywhere at any time. Cloud provides both software and hardware necessary to run various applications according to the needs of the user. To fulfil those needs of user internet connection is required to access the cloud. In...

In this paper, we present a novel multi-modal optimization algorithm for finding multiple local optima in objective function surfaces. We build from Species-based Particle Swarm Optimization (SPSO) by using deterministic sampling to generate new particles during the optimization process, by implementing proximity-based speciation coupled with speciation of isolated particles, and by including “...

In this paper an improved Particle Swarm Optimization (PSO) scheme is proposed to solve Static Routing and Wavelength Assignment (static RWA) where the movement of the swarm particles is influenced by their personal-best position searched so far and the position of the global-best particle. Simulation results show that the proposed scheme performs better in terms of particle fitness value and a...

Particle Swarm Optimization (PSO) is a simple but powerful optimization algorithm, introduced by Kennedy and Eberhart (Kennedy 1995). Its search for function optima is inspired by the behavior of flocks of birds looking for food. Similarly to birds, a set (swarm) of agents (particles) fly over the search space, which is coincident with the function domain, looking for the points where the funct...

In this paper, we present a new algorithm of swarm intelligence, namely, Cat Swarm Optimization (CSO). CSO is generated by observing the behaviors of cats, and composed of two sub-models, i.e., tracing mode and seeking mode, which model upon the behaviors of cats. Experimental results using six test functions demonstrate that CSO has much better performance than Particle Swarm Optimization (PSO).