Intro
Preface
Organization
Contents
Applications of Evolutionary Computation
An Enhanced Opposition-Based Evolutionary Feature Selection Approach
1 Introduction
2 Moth Flame Optimization
2.1 Binary Moth Flame Optimization
2.2 Binary Moth Flame Optimization for Feature Selection
3 The Proposed Approach
3.1 Initialization Using Opposition-Based Method
3.2 Retiring Flame
4 Experimental Setup and Results
5 Conclusions
References
A Methodology for Determining Ion Channels from Membrane Potential Neuronal Recordings
1 Introduction

2 Conductance-Based Model Description
3 Defining a Benchmark with Known Types of Ion Channels
4 Methodology and Experimental Setup
5 Experimental Results
6 Conclusions
A Mathematical Description of the Models
B Experimental Setup and Parameter Ranges
References
Swarm Optimised Few-View Binary Tomography
1 Introduction
2 Binary Tomographic Reconstruction
3 Swarm Optimisation
4 Constrained Search in High Dimensions
5 Reconstructions
6 Results
7 Discussion
8 Conclusions
References

Comparing Basin Hopping with Differential Evolution and Particle Swarm Optimization
1 Introduction
2 The Metaheuristics Studied
2.1 Basin Hopping
2.2 Differential Evolution
2.3 Particle Swarm Optimization
3 The Benchmarking Environment
4 Experimental Setup
5 Experimental Results
6 Conclusions
References
Combining the Properties of Random Forest with Grammatical Evolution to Construct Ensemble Models
1 Introduction
2 Methodology
2.1 Structured Grammatical Evolution
2.2 Random Structured Grammatical Evolution for Symbolic Regression Problems

3 Experimental Setup
3.1 Study Problems
3.2 Configuration of the Algorithms
4 Results
5 Conclusions
References
EvoCC: An Open-Source Classification-Based Nature-Inspired Optimization Clustering Framework in Python
1 Introduction
2 Related Works
3 Methodology
4 Framework Overview
4.1 Parameters
4.2 Datasets
4.3 Clustering with EvoCluster
4.4 Classification
4.5 Evaluation Measures
4.6 Results Management
5 Experiments and Visualizations
6 Conclusion and Future Works
References
Evolution of Acoustic Logic Gates in Granular Metamaterials

1 Introduction
2 Problem Statement
3 Simulation Setup
3.1 2D Granular Simulator
3.2 Optimization Method
4 Results and Discussion
4.1 Evolution of an Acoustic Band Gap
4.2 Evolving an AND Gate
4.3 Evolving an XOR Gate
5 Conclusion and Future Work
References
Public-Private Partnership: Evolutionary Algorithms as a Solution to Information Asymmetry
1 Introduction
2 The Problem
3 Proposed Approach
3.1 The Model
3.2 Data
3.3 Adversarial Optimization
3.4 Operator (EA1)
3.5 Public Administration (EA2)
4 Experimental Evaluation