reliability investigation has always been one of the most important issues in power systems planning. the outages rate in power system reflects the fact that more attentions should be paid on reliability indices to supply consumers with uninterrupted power. using reliability indices in economic dispatch problem may lead to the system load demand with high reliability and low probability of powe...

differential steering of in-wheel electric vehicle provides the functions of both active steering and power assisted steering with the coupling control of force and displacement transfer characteristic of system. a collaborative optimization model of the differential power-assisted steering system of in-wheel electric vehicle is built, with steering economy as the main system optimization goal,...

This paper presents a new optimization model – EPSO, Evolutionary Particle Swarm Optimization, inspired in both Evolutionary Algorithms and in Particle Swarm Optimization algorithms. The fundamentals of the method are described, and an application to the problem of Loss minimization and Voltage control is presented, with very good results.

In this paper, an effective combination of two Metaheuristic algorithms, namely Invasive Weed Optimization and the Particle Swarm Optimization, has been proposed. This hybridization called as HIWOPSO, consists of two main phases of Invasive Weed Optimization (IWO) and Particle Swarm Optimization (PSO). Invasive weed optimization is the natureinspired algorithm which is inspired by colonial beha...

This paper proposes a refined version of particle swarm optimization technique for the optimum design of steel structures. Swarm is composed of a number of particles and each particle in the swarm represents a candidate solution of the optimum design problem. Design constraints in accordance with ASD-AISC (Allowable Stress Design Code of American Institute of Steel Institution) are imposed by t...

This paper presents a new optimization model – EPSO, Evolutionary Particle Swarm Optimization, inspired in both Evolutionary Algorithms and in Particle Swarm Optimization algorithms. The fundamentals of the method are described, and an application to the problem of Loss minimization and Voltage control is presented, with very good results.

This paper presents a new variant of Particle Swarm Optimization algorithm named QPSO for solving global optimization problems. QPSO is an integrated algorithm making use of a newly defined, multiparent, quadratic crossover operator in the Basic Particle Swarm Optimization (BPSO) algorithm. The comparisons of numerical results show that QPSO outperforms BPSO algorithm in all the twelve cases ta...

Global optimization is an essential component of econometric modeling. Optimization in econometrics is often difficult due to irregular cost functions characterized by multiple local optima. The goal of this paper is to apply a relatively new stochastic global technique, particle swarm optimization, to the well-known but difficult disequilibrium problem. Because of its co-operative nature and b...