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Nature Inspired Cooperative Strategies for Optimization (NICSO 2013)

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Cover of 'Nature Inspired Cooperative Strategies for Optimization (NICSO 2013)'

Table of Contents

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    Book Overview
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    Chapter 1 Extending the ABC-Miner Bayesian Classification Algorithm
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    Chapter 2 A Multiple Pheromone Ant Clustering Algorithm
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    Chapter 3 An Island Memetic Differential Evolution Algorithm for the Feature Selection Problem
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    Chapter 4 Using a Scouting Predator-Prey Optimizer to Train Support Vector Machines with non PSD Kernels
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    Chapter 5 Response Surfaces with Discounted Information for Global Optima Tracking in Dynamic Environments
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    Chapter 6 Fitness Based Self Adaptive Differential Evolution
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    Chapter 7 Adaptation Schemes and Dynamic Optimization Problems: A Basic Study on the Adaptive Hill Climbing Memetic Algorithm
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    Chapter 8 Using Base Position Errors in an Entropy-Based Evaluation Function for the Study of Genetic Code Adaptability
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    Chapter 9 An Adaptive Multi-Crossover Population Algorithm for Solving Routing Problems
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    Chapter 10 Corner Based Many-Objective Optimization
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    Chapter 11 Escaping Local Optima via Parallelization and Migration
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    Chapter 12 An Improved Genetic Based Keyword Extraction Technique
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    Chapter 13 Part-of-Speech Tagging Using Evolutionary Computation
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    Chapter 14 A Cooperative Approach Using Ants and Bees for the Graph Coloring Problem
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    Chapter 15 Artificial Bee Colony Training of Neural Networks
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    Chapter 16 Nonlinear Optimization in Landscapes with Planar Regions
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    Chapter 17 Optimizing Neighbourhood Distances for a Variant of Fully-Informed Particle Swarm Algorithm
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    Chapter 18 Meta Morphic Particle Swarm Optimization
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    Chapter 19 Empirical Study of Computational Intelligence Strategies for Biochemical Systems Modelling
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    Chapter 20 Metachronal Waves in Cellular Automata: Cilia-Like Manipulation in Actuator Arrays
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    Chapter 21 Team of A-Teams Approach for Vehicle Routing Problem with Time Windows
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    Chapter 22 Self-adaptable Group Formation of Reconfigurable Agents in Dynamic Environments
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    Chapter 23 A Choice Function Hyper-heuristic for the Winner Determination Problem
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    Chapter 24 Automatic Generation of Heuristics for Constraint Satisfaction Problems
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    Chapter 25 Branching Schemes and Variable Ordering Heuristics for Constraint Satisfaction Problems: Is There Something to Learn?
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    Chapter 26 Nash Equilibria Detection for Discrete-Time Generalized Cournot Dynamic Oligopolies
Attention for Chapter 17: Optimizing Neighbourhood Distances for a Variant of Fully-Informed Particle Swarm Algorithm
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Chapter title
Optimizing Neighbourhood Distances for a Variant of Fully-Informed Particle Swarm Algorithm
Chapter number 17
Book title
Nature Inspired Cooperative Strategies for Optimization (NICSO 2013)
Published by
Springer International Publishing, January 2014
DOI 10.1007/978-3-319-01692-4_17
Book ISBNs
978-3-31-901691-7, 978-3-31-901692-4
Authors

Vytautas Jančauskas

Editors

German Terrazas, Fernando E. B. Otero, Antonio D. Masegosa