نتایج جستجو برای: modified pso

تعداد نتایج: 260689  

2014
A. Elsawaf

Particle swarm optimization (PSO) technique has achieved a considerable success in solving nonlinear, nondifferentiable, multi-modal optimization problems. Currently, PSO is broadly applied in several scientific and engineering optimization applications. This paper introduces an identification of magnetorheological (MR) damper’s parameters using the PSO algorithm to introduce a more simple and ...

2014
Paulus Mudjihartono

One of the challenging heuristic problems is that how to generate an academic timetable. Many searching methods have already been applied to take care of the problem but yet some drawbacks exist. The drawbacks are commonly about the convergence, the speed, and the effectiveness of the algorithm. This paper aims to apply modified Particle Swarm Optimization (PSO) to give a better solution rather...

Journal: :Expert Syst. Appl. 2012
Muhammad Ilyas Menhas Ling Wang Minrui Fei Hui Pan

In this paper, comparative performance analysis of various binary coded PSO algorithms on optimal PI and PID controller design for multiple inputs multiple outputs (MIMO) process is stated. Four algorithms such as modified particle swarm optimization (MPSO), discrete binary PSO (DBPSO), modified discrete binary PSO (MBPSO) and probability based binary PSO (PBPSO) are independently realized usin...

2011
Micael S. Couceiro N. M. Fonseca Ferreira Rui Rocha

The Darwinian Particle Swarm Optimization (DPSO) is an evolutionary algorithm that extends the well-known Particle Swarm Optimization (PSO) using natural selection, or survival-of-the-fittest, to enhance the ability to escape from local optima. In this paper, it is explored the effectiveness of using a modified version of both PSO and DPSO, respectively named as R-PSO and R-DPSO, on groups of s...

2013
Michal Pluhacek Roman Senkerik Ivan Zelinka Donald Davendra

A new promising strategy for the PSO (Particle swarm optimization) algorithm is proposed and described in this paper. This new strategy presents alternative way of assigning new velocity to each individual in particle swarm (population). This new multiple choice particle swarm optimization (MC-PSO) algorithm is tested on two different shifted test functions to show the performance on problems t...

2008
Jorge Isacc Flores-Mendoza Efrén Mezura-Montes

In this paper, the behavior of different Particle Swarm Optimization (PSO) variants is analyzed when solving a set of well-known numerical constrained optimization problems. After identifying the most competitive one, some improvements are proposed to this variant regarding the parameter control and the constraint-handling mechanism. Furthermore, the on-line behavior of the improved PSO and som...

2011
Laura Lanzarini Javier H. López Juan Andrés Maulini Armando De Giusti

Particle Swarm Optimization (PSO) is a metaheuristic that is highly used to solve monoand multi-objective optimization problems. Two well-differentiated PSO versions have been defined – one that operates in a continuous solution space and one for binary spaces. In this paper, a new version of the Binary PSO algorithm is presented. This version improves its operation by a suitable positioning of...

2008
Shahin Gheitanchi Falah Ali Elias Stipidis

Distributed processing is an essential part of collaborative computing techniques over ad-hoc networks. In this paper, a generalized particle swarm optimization (PSO) model for communication networks is introduced. A modified version of PSO, called trained PSO (TPSO), consisting of distributed particles that are adapted to reduce traffic and computational overhead of the optimization process is...

In this paper, optimal placement of Phasor Measurement Unit (PMU) using Global Positioning System (GPS) is discussed. Ant Colony Optimization (ACO), Simulated Annealing (SA), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) are used for this problem. Pheromone evaporation coefficient and the probability of moving from state x to state y by ant are introduced into the ACO. The modifi...

2010
Yuanxia Shen Guoyin Wang

Particle swarm optimization (PSO) has been shown to perform well on many optimization problems. However, the PSO algorithm often can not find the global optimum, even for unimodal functions. It is necessary to study the local search ability of PSO. The interval compression method and the probabilistic characteristic of the searching interval of particles are used to analyze the local search abi...

نمودار تعداد نتایج جستجو در هر سال

با کلیک روی نمودار نتایج را به سال انتشار فیلتر کنید