In this paper, a genetic algorithm and constriction factor based particle swarm optimization technique are proposed for solving the short term variable head hydrothermal scheduling problem with transmission line losses. The performance efficiency of the proposed techniques is demonstrated on hydrothermal test system comprising of two thermal units and two hydro power plants. the simulation resu...

Particle swarm optimization (PSO) has been successfully applied to solve various optimization problems. Recently, a state-based algorithm called multi-state particle swarm optimization (MSPSO) has been proposed to solve discrete combinatorial optimization problems. The algorithm operates based on a simplified mechanism of transition between two states. However, the MSPSO algorithm has to deal w...

Target search and trapping using self-organized swarm robots have received increasing attention in recent years but control design of these systems remains a challenge. In this paper, we propose a decentralized control algorithm of swarm robot for target search and trapping inspired by bacteria chemotaxis. First, a local coordinate system is established according to the initial positions of the...

The process of load balancing increases the performance of cloud based services. Cloud based service provide hardware, software and platform as service. For the balancing of public cloud used two types of approach one is traditional approach and other is dynamic approach. The traditional approach follows the concept of CPU scheduling technique such as round robin and first come first service. T...

A novel optimization algorithm, called accelerated particle swarm optimization (APSO), is proposed to be used for dynamic spectrum sensing in cognitive radio networks. While modified swarm-based optimization algorithms focus on slight variations of the standard mathematical formulas, in APSO, the acceleration variable of the particles is also considered in the search space. We show that the pro...

This paper try to solve the route optimization of stacker in automated storage and retrieval system with the hybrid algorithm which based on the combination of genetic algorithm and particle swarm optimization. First the algorithm generates the initial population by using particle swarm algorithm. And then the population undertakes assorted crossover and mutation in the iterative process by usi...

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. The Artificial Bee Colony algorithm is an optimization algorithm based on the intelligent behavior ...

Using Particle Swarm Optimization to handle complex functions with high-dimension it has the problems of low convergence speed and sensitivity to local convergence. The convergence of particle swarm algorithm is studied, and the condition for the convergence of particle swarm algorithm is given. Results of numerical tests show the efficiency of the results. Base on the idea of specialization an...

Cat Swarm Optimization (CSO) algorithm was put forward in 2006. Despite a faster convergence speed compared with Particle Swarm Optimization (PSO) algorithm, the application of CSO is greatly limited by the drawback of "premature convergence," that is, the possibility of trapping in local optimum when dealing with nonlinear optimization problem with a large number of local extreme values. In or...