Particle Swarm Optimization

Particle Swarm Optimization

Particle swarm optimization (PSO) was originally designed and introduced by Eberhart and Kennedy. The PSO is a population based search algorithm based on the simulation of the social behavior of birds, bees or a school of fishes. This algorithm originally intends to graphically simulate the graceful and unpredictable choreography of a bird folk. Each individual within the swarm is represented by a vector in multidimensional search space.

Description

This vector has also one assigned vector which determines the next movement of the particle and is called the velocity vector. The PSO algorithm also determines how to update the velocity of a particle. Each particle updates its velocity based on current velocity and the best position it has explored so far; and also based on the global best position explored by swarm.

Table of Contents

  • Novel Binary Particle Swarm Optimization
  • Swarm Intelligence Applications in Electric Machines
  • Particle Swarm Optimization for HW/SW Partitioning
  • Particle Swarms in Statistical Physics
  • Individual Parameter Selection Strategy for Particle Swarm Optimization
  • Personal Best Oriented Particle Swarm Optimizer
  • Particle Swarm Optimization for Power Dispatch with Pumped Hydro
  • Searching for the Best Points of Interpolation Using Swarm Intelligence Techniques
  • Particle Swarm Optimization and Other Metaheuristic Methods in Hybrid Flow Shop Scheduling Problem
  • A Particle Swarm Optimization Technique used for the Improvement of Analogue Circuit Performances
  • Particle Swarm Optimization Applied for Locating an Intruder by an Ultra-Wideband Radar Network
  • Application of Particle Swarm Optimization in Accurate Segmentation of Brain MR Images
  • Swarm Intelligence in Portfolio Selection
  • Enhanced Particle Swarm Optimization for Design and Optimization of Frequency Selective Surfaces and Artificial Magnetic Conductors
  • Search Performance Improvement for PSO in High Dimensional Space
  • Finding Base-Station Locations in Two-Tiered Wireless Sensor Networks by Particle Swarm Optimization
  • Particle Swarm Optimization Algorithm for Transportation Problems
  • A Particle Swarm Optimisation Approach to Graph Permutations
  • Particle Swarm Optimization Applied to Parameters Learning of Probabilistic Neural Networks for Classification of Economic Activities
  • Path Planning for Formations of Mobile Robots using PSO Technique
  • Simultaneous Perturbation Particle Swarm Optimization and Its FPGA Implementation
  • Particle Swarm Optimization with External Archives for Interactive Fuzzy Multiobjective Nonlinear Programming
  • Using Opposition-based Learning with Particle Swarm Optimization and Barebones Differential Evolution
  • Particle Swarm Optimization: Dynamical Analysis through Fractional Calculus
  • Discrete Particle Swarm Optimization Algorithm for Flowshop Scheduling
  • A Radial Basis Function Neural Network with Adaptive Structure via Particle Swarm Optimization
  • A Novel Binary Coding Particle Swarm Optimization for Feeder Reconfiguration
  • Application of Particle Swarm Optimization Algorithm in Smart Antenna Array Systems

Book Details

Author(s): Aleksandar Lazinica
Format(s): PDF, HTML
File size: 24.90 MB
Number of pages: 476
Link: Download.








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