Particle swarm optimization : theory, techniques, and applications
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Bibliographic Information
Particle swarm optimization : theory, techniques, and applications
（Engineering tools, techniques and tables series）
Nova Science Publishers, c2011
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Includes bibliographical references and index
Description and Table of Contents
Description
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.
Table of Contents
- 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.
by "Nielsen BookData"