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Bioinspired Optimization Methods and Their Applications

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Cover of 'Bioinspired Optimization Methods and Their Applications'

Table of Contents

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    Book Overview
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    Chapter 1 Optimization of Home Care Visits Schedule by Genetic Algorithm
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    Chapter 2 New Techniques for Inferring L-systems Using Genetic Algorithm
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    Chapter 3 An Adaptive Metaheuristic for Unconstrained Multimodal Numerical Optimization
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    Chapter 4 Scrum Task Allocation Based on Particle Swarm Optimization
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    Chapter 5 Cooperative Model for Nature-Inspired Algorithms in Solving Real-World Optimization Problems
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    Chapter 6 Collaborative Agent Teams (CAT): From the Paradigm to Implementation Guidelines
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    Chapter 7 A Bio-inspired Approach for Collaborative Exploration with Mobile Battery Recharging in Swarm Robotics
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    Chapter 8 Constructive Metaheuristics for the Set Covering Problem
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    Chapter 9 Single and Multiobjective Evolutionary Algorithms for Clustering Biomedical Information with Unknown Number of Clusters
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    Chapter 10 Evolutionary Algorithms for Scheduling of Crude Oil Preheating Process Under Linear Fouling
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    Chapter 11 Hybrid Weighted Barebones Exploiting Particle Swarm Optimization Algorithm for Time Series Representation
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    Chapter 12 Data-Driven Preference-Based Deep Statistical Ranking for Comparing Multi-objective Optimization Algorithms
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    Chapter 13 Construction of Heuristic for Protein Structure Optimization Using Deep Reinforcement Learning
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    Chapter 14 Comparing Boundary Control Methods for Firefly Algorithm
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    Chapter 15 A New Binary Encoding Scheme in Genetic Algorithm for Solving the Capacitated Vehicle Routing Problem
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    Chapter 16 Ensemble and Fuzzy Techniques Applied to Imbalanced Traffic Congestion Datasets: A Comparative Study
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    Chapter 17 Multi-objective Design of Time-Constrained Bike Routes Using Bio-inspired Meta-heuristics
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    Chapter 18 Ensemble of Kriging with Multiple Kernel Functions for Engineering Design Optimization
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    Chapter 19 Path Planning Optimization Method Based on Genetic Algorithm for Mapping Toxic Environment
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    Chapter 20 Tuning Multi-Objective Optimization Algorithms for the Integration and Testing Order Problem
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    Chapter 21 Surrogate-Assisted Particle Swarm with Local Search for Expensive Constrained Optimization
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    Chapter 22 Indicator-Based Versus Aspect-Based Selection in Multi- and Many-Objective Biochemical Optimization
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    Chapter 23 An Approach for Recovering Distributed Systems from Disasters
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    Chapter 24 Population Diversity Analysis for the Chaotic Based Selection of Individuals in Differential Evolution
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    Chapter 25 Robust Design with Surrogate-Assisted Evolutionary Algorithm: Does It Work?
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    Chapter 26 How Distance Based Parameter Adaptation Affects Population Diversity
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    Chapter 27 Collaborative Variable Neighborhood Search
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Title
Bioinspired Optimization Methods and Their Applications
Published by
Springer International Publishing, June 2018
DOI 10.1007/978-3-319-91641-5
ISBNs
978-3-31-991640-8, 978-3-31-991641-5
Editors

Korošec, Peter, Melab, Nouredine, Talbi, El-Ghazali

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The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 37 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 5%
Student > Master 2 5%
Student > Doctoral Student 1 3%
Professor 1 3%
Unknown 31 84%
Readers by discipline Count As %
Computer Science 3 8%
Engineering 3 8%
Unknown 31 84%