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Particle Swarm Optimization
Edited by Aleksandar Lazinica, ISBN 978-953-7619-48-0, Hard cover, 476 pages, Publisher: InTech, Published: January 01, 2009 under CC BY-NC-SA 3.0 license, in subject Numerical Analysis and Scientific Computing
DOI: 10.5772/109
Particle swarm optimization (PSO) is a population based stochastic optimization technique influenced by the social behavior of bird flocking or fish schooling.PSO shares many similarities with evolutionary computation techniques such as Genetic Algorithms (GA). The system is initialized with a population of random solutions and searches for optima by updating generations. However, unlike GA, PSO has no evolution operators such as crossover and mutation. In PSO, the potential solutions, called particles, fly through the problem space by following the current optimum particles. This book represents the contributions of the top researchers in this field and will serve as a valuable tool for professionals in this interdisciplinary field.
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Book contents
- Chapter 1Novel Binary Particle Swarm Optimization
- Chapter 2Swarm Intelligence Applications in Electric Machines
- Chapter 3Particle Swarm Optimization for HW/SW Partitioning
- Chapter 4Particle Swarms in Statistical Physics
- Chapter 5Individual Parameter Selection Strategy for Particle Swarm Optimization
- Chapter 6Personal Best Oriented Particle Swarm Optimizer
- Chapter 7Particle Swarm Optimization for Power Dispatch with Pumped Hydro
- Chapter 8Searching for the Best Points of Interpolation Using Swarm Intelligence Techniques
- Chapter 9Particle Swarm Optimization and Other Metaheuristic Methods in Hybrid Flow Shop Scheduling Problem
- Chapter 10A Particle Swarm Optimization Technique used for the Improvement of Analogue Circuit Performances
- Chapter 11Particle Swarm Optimization Applied for Locating an Intruder by an Ultra-Wideband Radar Network
- Chapter 12Application of Particle Swarm Optimization in Accurate Segmentation of Brain MR Images
- Chapter 13Swarm Intelligence in Portfolio Selection
- Chapter 14Enhanced Particle Swarm Optimization for Design and Optimization of Frequency Selective Surfaces and Artificial Magnetic Conductors
- Chapter 15Search Performance Improvement for PSO in High Dimensional Space
- Chapter 16Finding Base-Station Locations in Two-Tiered Wireless Sensor Networks by Particle Swarm Optimization
- Chapter 17Particle Swarm Optimization Algorithm for Transportation Problems
- Chapter 18A Particle Swarm Optimisation Approach to Graph Permutations
- Chapter 19Particle Swarm Optimization Applied to Parameters Learning of Probabilistic Neural Networks for Classification of Economic Activities
- Chapter 20Path Planning for Formations of Mobile Robots using PSO Technique
- Chapter 21Simultaneous Perturbation Particle Swarm Optimization and Its FPGA Implementation
- Chapter 22Particle Swarm Optimization with External Archives for Interactive Fuzzy Multiobjective Nonlinear Programming
- Chapter 23Using Opposition-based Learning with Particle Swarm Optimization and Barebones Differential Evolution
- Chapter 24Particle Swarm Optimization: Dynamical Analysis through Fractional Calculus
- Chapter 25Discrete Particle Swarm Optimization Algorithm for Flowshop Scheduling
- Chapter 26A Radial Basis Function Neural Network with Adaptive Structure via Particle Swarm Optimization
- Chapter 27A Novel Binary Coding Particle Swarm Optimization for Feeder Reconfiguration
- Chapter 28Application of Particle Swarm Optimization Algorithm in Smart Antenna Array Systems
