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Foundations of Computational Intelligence Volume 3

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Cover of 'Foundations of Computational Intelligence Volume 3'

Table of Contents

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    Book Overview
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    Chapter 1 Genetic Algorithms for the Use in Combinatorial Problems
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    Chapter 2 Bacterial Foraging Optimization Algorithm: Theoretical Foundations, Analysis, and Applications
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    Chapter 3 Global Optimization Using Harmony Search: Theoretical Foundations and Applications
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    Chapter 4 Hybrid GRASP Heuristics
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    Chapter 5 Particle Swarm Optimization: Performance Tuning and Empirical Analysis
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    Chapter 6 Tabu Search to Solve Real-Life Combinatorial Optimization Problems: A Case of Study
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    Chapter 7 Reformulations in Mathematical Programming: A Computational Approach
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    Chapter 8 Graph-Based Local Elimination Algorithms in Discrete Optimization
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    Chapter 9 Evolutionary Approach to Solving Non-stationary Dynamic Multi-Objective Problems
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    Chapter 10 Turbulent Particle Swarm Optimization Using Fuzzy Parameter Tuning
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    Chapter 11 An Evolutionary Approximation for the Coefficients of Decision Functions within a Support Vector Machine Learning Strategy
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    Chapter 12 Evolutionary Computing in Statistical Data Analysis
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    Chapter 13 Meta-heuristics for System Design Engineering
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    Chapter 14 Transgenetic Algorithm: A New Endosymbiotic Approach for Evolutionary Algorithms
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    Chapter 15 Multi-objective Team Forming Optimization for Integrated Product Development Projects
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    Chapter 16 Genetic Algorithms for Task Scheduling Problem
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    Chapter 17 PSO_Bounds: A New Hybridization Technique of PSO and EDAs
Attention for Chapter 2: Bacterial Foraging Optimization Algorithm: Theoretical Foundations, Analysis, and Applications
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