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...

This paper presents a new multi-objective optimization algorithm in which multi-swarm cooperative strategy is incorporated into particle swarm optimization algorithm, called multi-swarm cooperative multi-objective particle swarm optimizer (MC-MOPSO). This algorithm consists of multiple slave swarms and one master swarm. Each slave swarm is designed to optimize one objective function of the mult...

one of the most important applications of multi-objective optimization is adjusting parameters ofpractical engineering problems in order to produce a more desirable outcome. in this paper, the decoupled sliding mode control technique (dsmc) is employed to stabilize an inverted pendulum which is a classic example of inherently unstable systems. furthermore, a new multi-objective particle swarm o...

cementation factor is a critical parameter, which affects water saturation calculation. in carbonate rocks, due to the sensitivity of this parameter to pore type, water saturation estimation has associated with high inaccuracy. hence developing a reliable mathematical strategy to determine these properties accurately is of crucial importance. to this end, genetic algorithm pattern search is emp...

the purpose of load frequency control is to reduce transient oscillation frequencies than its nominal valueand achieve zero steady-state error for it.a common technique used in real applications is to use theproportional integral controller (pi). but this controller has a longer settling time and a lot of extramutation in output response of system so it required that the parameters be adjusted ...

In this paper, a chaotic particle swarm optimization with mutation-based classifier particle swarm optimization is proposed to classify patterns of different classes in the feature space. The introduced mutation operators and chaotic sequences allows us to overcome the problem of early convergence into a local minima associated with particle swarm optimization algorithms. That is, the mutation ...

flexible ac transmission systems (facts) controllers with its ability to directly control the power flow can offer great opportunities in modern power system, allowing better and safer operation of transmission network. in this paper, in order to find type, size and location of facts devices in a power system a dedicated improved particle swarm optimization (dipso) algorithm is developed for de...

Particle Swarm Optimization algorithm is based on iterative optimization tools, system initialization of a group of random solutions, through iterative search for the optimal value. The basic idea of the fuzzy C-means clustering algorithm is to determine each sample data belonging to a certain degree of clustering, and the degree of membership of sample data is grouped into a cluster. Favor opt...