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Advances in Metaheuristics for Hard Optimization

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Cover of 'Advances in Metaheuristics for Hard Optimization'

Table of Contents

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    Book Overview
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    Chapter 1 Comparison of Simulated Annealing, Interval Partitioning and Hybrid Algorithms in Constrained Global Optimization
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    Chapter 2 Four-bar Mechanism Synthesis for n Desired Path Points Using Simulated Annealing
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    Chapter 3 “MOSS-II” Tabu/Scatter Search for Nonlinear Multiobjective Optimization
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    Chapter 4 Feature Selection for Heterogeneous Ensembles of Nearest-neighbour Classifiers Using Hybrid Tabu Search
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    Chapter 5 A Parallel Ant Colony Optimization Algorithm Based on Crossover Operation
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    Chapter 6 An Ant-bidding Algorithm for Multistage Flowshop Scheduling Problem: Optimization and Phase Transitions
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    Chapter 7 Dynamic Load Balancing Using an Ant Colony Approach in Micro-cellular Mobile Communications Systems
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    Chapter 8 New Ways to Calibrate Evolutionary Algorithms
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    Chapter 9 Divide-and-Evolve: a Sequential Hybridization Strategy Using Evolutionary Algorithms
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    Chapter 10 Local Search Based on Genetic Algorithms
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    Chapter 11 Designing Efficient Evolutionary Algorithms for Cluster Optimization: A Study on Locality
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    Chapter 12 Aligning Time Series with Genetically Tuned Dynamic Time Warping Algorithm
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    Chapter 13 Evolutionary Generation of Artificial Creature’s Personality for Ubiquitous Services
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    Chapter 14 Some Guidelines for Genetic Algorithm Implementation in MINLP Batch Plant Design Problems
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    Chapter 15 Coevolutionary Genetic Algorithm to Solve Economic Dispatch
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    Chapter 16 An Evolutionary Approach to Solve a Novel Mechatronic Multiobjective Optimization Problem
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    Chapter 17 Optimizing Stochastic Functions Using a Genetic Algorithm: An Aeronautic Military Application
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    Chapter 18 Learning Structure Illuminates Black Boxes – An Introduction to Estimation of Distribution Algorithms
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    Chapter 19 Making a Difference to Differential Evolution
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    Chapter 20 Hidden Markov Models Training Using Population-based Metaheuristics
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    Chapter 21 Inequalities and Target Objectives for Metaheuristic Search – Part I: Mixed Binary Optimization
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Citations

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Readers on

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54 Mendeley
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Title
Advances in Metaheuristics for Hard Optimization
Published by
Springer-Verlag Berlin Heidelberg, January 2008
DOI 10.1007/978-3-540-72960-0
ISBNs
978-3-54-072959-4, 978-3-54-072960-0, 978-3-64-209206-0
Editors

Patrick Siarry, Zbigniew Michalewicz

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 54 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 4%
Unknown 52 96%
Readers by discipline Count As %
Computer Science 1 2%
Social Sciences 1 2%
Unknown 52 96%

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