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Handbook of Swarm Intelligence

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Cover of 'Handbook of Swarm Intelligence'

Table of Contents

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    Book Overview
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    Chapter 1 From Theory to Practice in Particle Swarm Optimization
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    Chapter 2 What Makes Particle Swarm Optimization a Very Interesting and Powerful Algorithm?
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    Chapter 3 Developing Niching Algorithms in Particle Swarm Optimization
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    Chapter 4 Test Function Generators for Assessing the Performance of PSO Algorithms in Multimodal Optimization
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    Chapter 5 Linkage Sensitive Particle Swarm Optimization
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    Chapter 6 Parallel Particle Swarm Optimization Algorithm Based on Graphic Processing Units
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    Chapter 7 Velocity Adaptation in Particle Swarm Optimization
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    Chapter 8 Integral-Controlled Particle Swarm Optimization
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    Chapter 9 Particle Swarm Optimization for Markerless Full Body Motion Capture
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    Chapter 10 An Adaptive Multi-Objective Particle Swarm Optimization Algorithm with Constraint Handling
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    Chapter 11 Multiobjective Particle Swarm Optimization for Optimal Power Flow Problem
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    Chapter 12 A Multi-objective Resource Assignment Problem in Product Driven Supply Chain Using Quantum Inspired Particle Swarm Algorithm
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    Chapter 13 Honeybee Optimisation – An Overview and a New Bee Inspired Optimisation Scheme
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    Chapter 14 Parallel Approaches for the Artificial Bee Colony Algorithm
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    Chapter 15 Bumble Bees Mating Optimization Algorithm for the Vehicle Routing Problem
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    Chapter 16 Ant Colony Optimization: Principle, Convergence and Application
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    Chapter 17 Optimization of Fuzzy Logic Controllers for Robotic Autonomous Systems with PSO and ACO
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    Chapter 18 A New Framework for Optimization Based-On Hybrid Swarm Intelligence
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    Chapter 19 Glowworm Swarm Optimization for Multimodal Search Spaces
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    Chapter 20 Direct and Inverse Modeling of Plants Using Cat Swarm Optimization
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    Chapter 21 Parallel Bacterial Foraging Optimization
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    Chapter 22 Reliability-Redundancy Optimization Using a Chaotic Differential Harmony Search Algorithm
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    Chapter 23 Gene Regulatory Network Identification from Gene Expression Time Series Data Using Swarm Intelligence
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