[PDF] Top 20 A particle swarm optimizer for multi-objective optimization
Has 10000 "A particle swarm optimizer for multi-objective optimization" found on our website. Below are the top 20 most common "A particle swarm optimizer for multi-objective optimization".
A particle swarm optimizer for multi-objective optimization
... The remainder of the paper is organized as follows: Section 2 gives a brief description of the most relevant previous work. Section 3 reviews the basic concepts of multi-objective optimization. ... See full document
12
A particle swarm optimizer for multi-objective optimization
... unique equal size k−dimensional hypercubes (d is a user parameter and k is the number of objective functions). The stored solutions are placed in one of these hypercubes according to their locations in the ... See full document
7
Multi-objective optimization with a Gaussian PSO algorithm
... the particle swarm is initialized with random values corresponding to the ranges (depending on the test functions) and the velocities are initialized with zero values (lines ...the swarm is evaluated ... See full document
12
The Optimal combination: Grammatical Swarm, Particle Swarm Optimization and Neural Networks.
... done for every dimensión, the mutated one is evaluated with the fitness function, and then compared it to the evaluation of the non-mutated one, ...current particle. If it is smaller, then the mutated ... See full document
10
Identification of intermediate debonding damage in FRP-plated RC beams based on multi-objective particle swarm optimization without updated baseline model
... Specifically, two damage scenarios (different locations and degrees of damage) were considered. A sin- gle damage scenario due to a debonded area at the FRP-concrete interface of lengt[r] ... See full document
12
Polynomial approximation using particle swarm optimization of lineal enhanced neural networks with no hidden layers.
... unconstrained optimization problem in discrete or continuous variable, the multi target problem and the constrained problem have been ...results for training Artificial Neural ... See full document
17
Multicast routing and wavelength assignment in optical networks with particle swarm optimization
... looked for an optimization of the generated traffic weighted sum, the hop count and other objective ...algorithm for the simultaneous optimization of the number of wavelengths and the ... See full document
10
A Study of Archiving Strategies in Multi-Objective PSO for Molecular Docking
... a Multi-Objective Particle Swarm Optimization (MOPSO) charac- terized by two features: a velocity constraint mechanism and an external bounded archive to store the non-dominated ... See full document
12
Particle swarm optimization para un problema de optimización combinatoria
... “Particle Swarm Optimization for Sequencing Problems: A Case Study”, Congress on Evolutionary Computation, pags 536-541, 2004, Portland, Oregon, ...New Optimizer Using Particles ... See full document
9
Metaheurísticas poblacionales aplicadas a la resolución de problemas complejos
... (Multi Objective Particle Swarm Optimization) [19], teniendo en consideración como premisas centrales de trabajo la manutención de la diversidad en la población, así como la eficiencia ... See full document
5
Global numerical optimization with a bi-population particle swarm optimizer
... named particle and represents a possible solution within a multidimen- sional search ...competitive for solving unconstrained real-world optimization prob- lems [15, 16, 9, 3, ...strongly ... See full document
12
Differential Evoluiton - Particle Swarm Optimization
... Once the new trial vector z is created, the algorithm has to decide whether or not it should become a member of the new generation (or otherwise known as iteration t+1). This is done by comparing fitness values with the ... See full document
11
Optimization of the hydrolysis of lignocellulosic residues by using radial basis functions modeling and particle swarm optimization
... [11] Giordano PC, Martínez HD, Iglesias AA, Beccaria AJ, Goicoechea HC. Application of response surface methodology and artificial neural networks for optimization of recombinant Oryza sativa non-symbiotic ... See full document
31
Optimización multi-objetivo en las ciencias de la vida.
... or multi-objective optimization, the second one is completely specific for multi-objective ...objectives for the subsequent decision-making by the expert and, on the other ... See full document
75
Computer Science & Technology Series . XX Argentine Congress of Computer Science. Selected papers
... Bovine Identification is based on different methods such as ear, neck and brisket tags, tattoos, hot and cold branding and ear notches. Some of these methods are susceptible to loss, theft and tampering, while others ... See full document
314
Particle swarm optimization aplicado a la programación de los ciclos de semáforos en Bahía Blanca
... El ´area urbana seleccionada se en- cuentra enmarcada por la Plaza Ri- vadavia, esta plaza se encuentra situada en el centro comercial de la ciudad de Bah´ıa Blanca (Figu- ra 2). Se seleccionaron 53 intersec- ciones a su ... See full document
10
Particle Swarm Optimization and Uncertainty Assessment in Inverse Problems
... used for sampling using different basis ...used for sampling ...used for instance in [3,30] using approximate solution methods. For very high dimensional inverse problems, it is compulsory to ... See full document
14
Multi Objective Optimization Using Ants Colony for Placed Capacitors on Distribution Systems
... capacitors optimization methodology with multi objective ...first objective is the reduction of power losses, and the second is the investment ...colony optimization is used, adapting ... See full document
6
Comparación de algoritmos evolutivos para la optimización en la clasificación de la obesidad en escolares
... Encoding Particle Swarm Optimization (REPSO-C), Incremental Learning with Genetic Algorithms (ILGA) and Decision Tree with Genetic Algorithm (DT-GA) to determine the percent improvement during each ... See full document
18
CALIBRATION OF SEMI ANALYTIC MODELS OF GALAXY FORMATION USING PARTICLE SWARM OPTIMIZATION
... interval for each of the ...allowing for best initial guess of the behaviour ( quan- ti fi ed, in our case, by the fi tness function used ) of the whole parameter ...example for a two-dimensional ... See full document
10
Related subjects