Particle swarm optimisation : classical and quantum optimisation

 Content: Introduction Optimisation Problems and Optimisation Methods Random Search Techniques Metaheuristic Methods Swarm Intelligence  Particle Swarm Optimisation Overview Motivations PSO Algorithm: Basic Concepts and the Procedure Paradigm: How to Use PSO to Solve Optimisation Problems Some Harder Examples   Some Variants of Particle Swarm Optimisation  Why Does the PSO Algorithm Need to Be Improved?  Inertia and Constriction-Acceleration Techniques for PSO Local Best Model Probabilistic Algorithms Other Variants of PSO   Quantum-Behaved Particle Swarm Optimisation  Overview Motivation: From Classical Dynamics to Quantum Mechanics Quantum Model: Fundamentals of QPSO QPSO Algorithm Some Essential Applications Some Variants of QPSO Summary   Advanced Topics  Behaviour Analysis of Individual Particles Convergence Analysis of the Algorithm Time Complexity and Rate of Convergence Parameter Selection and Performance Summary  Industrial Applications  Inverse Problems for Partial Differential Equations Inverse Problems for Non-Linear Dynamical Systems Optimal Design of Digital Filters ED Problems MSA Image Segmentation Image Fusion  Index  References appear at the end of each chapter.