Particle swarm optimization : theory, techniques, and applications

著者

    • Olsson, Andrea E.

書誌事項

Particle swarm optimization : theory, techniques, and applications

Andrea E. Olsson, editor

（Engineering tools, techniques and tables series）

Nova Science Publishers, c2011

大学図書館所蔵 件 / 全4件

この図書・雑誌をさがす

注記

Includes bibliographical references and index

内容説明・目次

内容説明

Particle swarm optimisation (PSO) is an algorithm modelled on swarm intelligence that finds a solution to an optimisation problem in a search space or model and predicts social behaviour in the presence of objectives. The PSO is a stochastic, population-based computer algorithm modelled on swarm intelligence. Swarm intelligence is based on social-psychological principles and provides insights into social behaviour, as well as contributing to engineering applications. This book presents information on particle swarm optimisation such as using mono-objective and multi-objective particle swarm optimisation for the tuning of process control laws; convergence issues in particle swarm optimisation; study on vehicle routing problems using enhanced particle swarm optimisation and others.

目次

  • Preface
  • Using Mono-Objective & Multi-Objective Particle Swarm Optimization for the Tuning of Process Control Laws
  • Study on Vehicle Routing Problem with Time Windows Based on Enhanced Particle Swarm Optimization Approach
  • Reliability Optimization Problems using Adaptive Genetic Algorithm & Improved Particle Swarm Optimization
  • Convergence Issues in Particle Swarm Optimization
  • Globally Convergent Modifications of Particle Swarm Optimization for Unconstrained Optimization
  • Nonlinear 0-1 Programming through Particle Swarm Optimization using Decoding Algorithms
  • Comparative Study of Different Approaches to Particle Swarm Optimization in Theory & Practice
  • Particle Swarm Optimization for Computer Graphics & Geometric Modeling: Recent Trends
  • The Singly-Linked Ring Topology for the Particle Swarm Optimization Algorithm
  • PSO Assisted Multiuse Detection for DS-CDMA Communication Systems
  • Optimization of Abrasive Flow Machining Process Parameters using Particle Swarm Optimization & Simulated Annealing Algorithms
  • Index.

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