Particle Swarm Optimization is currently employed in several optimization and search problems due its ease and ability to find solutions successfully. A variant of PSO, called as Improved PSO has been developed in this paper and is hybridized with the simulated annealing approach to achieve better solutions. The hybrid technique has been employed, inorder to improve the performance of improved ...

The basic theories, development and applications of particle swarm optimization and genetic algorithm are introducedd.Some models of improved PSO algorithms are outlined. Characteristics of PSO and GA are compared. Two methods of hybrid of PSO and GA at present was summarized:hybrid with two algorithms entirely or with only a few steps ,and illustrated with flowchart.Limitation of two methods o...

QoS multicast routing is a non-linear combinatorial optimization problem that arises in many multimedia applications. Providing QoS support is crucial to guarantee effective transportation of multimedia service in multicast communication. Computing the band-widthdelay constrained least cost multicast routing tree is an NP-complete problem. In this paper, a novel heuristic QoS multicast routing ...

In this paper, a two-phase hybrid particle swarm optimization (PSO) approach is used to solve optimal reactive power dispatch (ORPD) problem. In this hybrid approach, PSO is used to explore the optimal region and direct search is used as local optimization technique for finer convergence. The performance of the proposed hybrid approach is demonstrated with the IEEE 30-bus and IEEE 57-bus system...

This paper proposes a hybrid Particle Swarm Optimization (PSO) method, which is based on the fusion of the PSO, Clonal Selection Algorithm (CSA), and Mind Evolutionary Computation (MEC). The clone function borrowed from the CSA and MEC-characterized similartaxis and dissimilation operations are embedded in the original PSO algorithm. Simulations of nonlinear function optimization are made to co...

FACTS devices plays a significant role to control the power flow of power transmission system. In this paper, a hybrid PSO algorithm is proposed to optimize the location of UPFC in power system. The proposed hybrid PSO algorithm has solved the formulated multiobjective optimization problem. This paper, five objective function to be considered in the form of minimization such as the fast voltage...

Many heuristic-based approaches have been applied to finding schedules that minimize the execution time of computing tasks on parallel processors. Particle Swarm Optimization is currently employed in several optimization and search problems due its ease and ability to find solutions successfully. A variant of PSO, called as Improved PSO has been developed in this paper and is hybridized with th...

In this paper, hybrid particle swarm optimization (PSO) is proposed for solving the challenging multi-contingency transient stability constrained optimal power flow (MC-TSCOPF) problem. The objective of this nonlinear optimization problem is to minimize the total fuel cost of the system and at the same time fulfil the transient stability requirements. The optimal power flow (OPF) with transient...

A hybrid meta-heuristic optimization method is introduced to efficiently find the optimal shape of concrete gravity dams including dam-water-foundation rock interaction subjected to earthquake loading. The hybrid meta-heuristic optimization method is based on a hybrid of gravitational search algorithm (GSA) and particle swarm optimization (PSO), which is called GSA-PSO. The operation of GSA-PSO...

Particle Swarm Optimization (PSO) has shown good performance in many optimization problems. However, it easily falls into local optima and suffers from premature convergence on complex multimodal problems. To help trapped particles escape from local minima, a novel hybrid jumps strategy is proposed. The main idea of the new jump strategy is to monitor the changes of previous best particle and t...