Constrained MPC with modified particle swarm optimization
A Modified Particle Swarm Optimization Algorithm
... the particle can search more ...the particle which has the best value in last iteration would be smaller than last times, and it is acceptable the fitness is worse in a lim- ited extent ...
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A Modified Particle Swarm Optimization Algorithm
... a particle chooses its inertial factor according to the approaching degree between the fitness of itself and the optimal particle, a modified particle swarm optimization ...
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Constrained Fuzzy Predictive Control Using Particle Swarm Optimization
... using particle swarm optimization (PSO) approach is ...complex optimization problem with minimal computational ...dynamic optimization problem changes are ...
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Constrained Optimal Power Flow using Particle Swarm Optimization
... ARTICLE SWARM OPTIMIZATION Particle swarm optimization (PSO) is a population based stochastic optimization technique inspired by social behavior of bird flocking or fish ...
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Improved Particle Swarm Optimization in Constrained Numerical Search Spaces
... with constrained search spaces, which in fact may produce a more complex technique, in this work a preliminary analysis of the behavior of the most known PSO variants was performed as to get an adequate search ...
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Empirical Study of an Unconstrained Modified Particle Swarm Optimization
... is modified by its own inertia. In this paper, an unconstrained modified version of the canonical PSO is presented ...a modified version of the canonical PSO with no constraints of maximum velocity, ...
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A modified particle swarm optimization algorithm for location problem
... Abstract. In the Weber location problem which was proposed for optimal location of industrial enterprises, the aim is to find the location of a point such that the sum of weighted distance between this point and a finite ...
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A modified particle swarm optimization via particle visual modeling analysis
... the optimization process [ 8 , 9 ...individual particle for the purpose of exploring the behavior of the individual particle’s movement in the search space; hence, obtaining more information about the ...
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A Modified Particle Swarm Optimization Algorithm for Reliability Redundancy Optimization Problem
... a modified particle swarm optimization (MPSO) algorithm to solve the reliability– redundancy optimization ...each particle is generated by using difference ...complex ...
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Solving Engineering Optimization Problems with the Simple Constrained Particle Swarm Optimizer
... design optimization problems was chosen to evaluate the performance of our proposed algo- ...parameters: swarm size = 8 particles, neighborhood size = 3, inertia factor w = ...
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A hybrid particle swarm evolutionary algorithm for constrained multi-objective optimization
... in constrained MOPs [20]. In this paper, we develop a hybrid particle swam evolutionary algorithm to solve constrained ...during optimization which can avoid premature ...
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Stopping Criteria for a Constrained Single-Objective Particle Swarm Optimization Algorithm
... Keywords: constrained single-objective optimization, evolutionary algorithms, particle swarm optimization, stopping criteria Received: November 3, 2006 When using optimization ...
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Improved Constrained Portfolio Selection Model using Particle Swarm Optimization
... of particle swarm optimization algorithm was engaged and genetic algorithm to make a comparison of the results ...between particle swarm optimization algorithm and genetic ...
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Opposition-Based Barebones Particle Swarm for Constrained Nonlinear Optimization Problems
... a modified barebones particle swarm optimization OBPSO to solve con- strained nonlinear optimization ...barebones particle swarm optimization BPSO and ...
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CiteSeerX — The SVM Classifier Based on the Modified Particle Swarm Optimization
... As a result of the SVM classifier training the support vectors must be determined. These vectors are closest to the hyperplane separating the classes and contain all information about the classes’ separation. The main ...
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Image classification technique using modified particle swarm optimization
... 4. Experimental Design and Results To thoroughly investigate the performance of the proposed modified PSO algorithm, we have conducted experiments with it on a number of datasets. The datasets are taken from ...
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SOLVING CARDINALITY CONSTRAINED PORTFOLIO OPTIMIZATION PROBLEM BY BINARY PARTICLE SWARM OPTIMIZATION ALGORITHM
... 3. Application part – efficient frontier estimation In this section the efficient frontier of constrained portfolio optimization problem defined by Problem P2 is searched. Used data consists of two ...
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Constrained Motion Particle Swarm Optimization for Non-Linear Time Series Prediction
... 63 and will not be necessary to include in the optimization parameter list. The calculation of b is discussed in the next section. The PSO algorithm is an iterative process, as it tries to find a set of parameters ...
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A modified particle swarm optimization algorithm for parameter estimation of a biological system
... ith particle is then updated by the following formula: P ij ð Þ ¼ t P ij ð t−1 Þ þ V ij ð Þ t ð17Þ The PSO algorithm is known as a fast simple method, suitable for non-convex NP-hard problems such as bio- logical ...
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Modified Particle Swarm Optimization using Nonlinear Decreased Inertia Weight
... Abstract Particle Swarm Optimization (PSO) has demonstrated great performance in various optimization ...a Modified Particle Swarm Optimization (MPSO) using ...
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