Benchmarks and Hybrid Algorithms in Optimization and Applications (Springer Tracts in Nature-Inspired Computing)

✍ Scribed by Xin-She Yang (editor)

• Publisher: Springer
• Year: 2023
• Tongue: English
• Leaves: 250
• Category: Library

✦ Synopsis

This book is specially focused on the latest developments and findings on hybrid algorithms and benchmarks in optimization and their applications in sciences, engineering, and industries. The book also provides some comprehensive reviews and surveys on implementations and coding aspects of benchmarks. The book is useful for Ph.D. students and researchers with a wide experience in the subject areas and also good reference for practitioners from academia and industrial applications.

✦ Table of Contents

Preface
Contents
1 Nature-Inspired Algorithms in Optimization: Introduction, Hybridization, and Insights
1 Introduction
2 Optimization and Algorithms
2.1 Components of Optimization
2.2 Gradients and Optimization
3 Nature-Inspired Algorithms
3.1 Recent Nature-Inspired Algorithms
3.2 Other Nature-inspired Algorithms
4 Hybridization
4.1 Hybridization Schemes
4.2 Issues and Warnings
5 Insights and Recommendations
References
2 Ten New Benchmarks for Optimization
1 Introduction
2 Role of Benchmarks
3 New Benchmark Functions
3.1 Noisy Functions
3.2 Non-differentiable Functions
3.3 Functions with Isolated Domains
4 Benchmarks with Multiple Optimal Solutions
4.1 Function on a Hyperboloid
4.2 Non-smooth Multi-layered Functions
5 Parameter Estimation as Benchmarks
6 Integrals as Benchmarks
7 Benchmarks of Infinite Dimensions
7.1 Shortest Path Problem
7.2 Shape Optimization
8 Conclusions
References
3 Review of Parameter Tuning Methods for Nature-Inspired Algorithms
1 Introduction
2 Parameter Tuning
2.1 Schematic Representation of Parameter Tuning
2.2 Different Types of Optimality
2.3 Approaches to Parameter Tuning
3 Review of Parameter Tuning Methods
3.1 Generic Methods for Parameter Tuning
3.2 Online and Offline Tunings
3.3 Self-Parametrization and Fuzzy Methods
3.4 Machine Learning-Based Methods
4 Discussions and Recommendations
References
4 QOPTLib: A Quantum Computing Oriented Benchmark for Combinatorial Optimization Problems
1 Introduction
2 Description of the Problems
2.1 Traveling Salesman Problem
2.2 Vehicle Routing Problem
2.3 Bin Packing Problem
2.4 Maximum Cut Problem
3 Introducing the Generated QOPTLib Benchmarks
4 Preliminary Experimentation
5 Conclusions and Further Work
References
5 Benchmarking for Discrete Cuckoo Search: Three Case Studies
1 Introduction
2 COPs Statements
2.1 Studied COPs
2.2 Formal Definitions
3 DCS Common Resolution
3.1 General Algorithm
3.2 Main Functions
4 Studied Case Resolutions
4.1 Solutions
4.2 Moves
5 Experimental Tests
5.1 Parameters
5.2 Instances
5.3 Statistic Tests
6 Conclusion
References
6 Metaheuristics for Feature Selection: A Comprehensive Comparison Using Opytimizer
1 Introduction
2 Literature Review
3 Hands-on Opytimizer: A Python Implementation for Metaheuristic Optimization
4 Case Study: Feature Selection
4.1 Methodology
4.2 Experiments
5 Conclusions
References
7 AL4SLEO: An Active Learning Solution for the Semantic Labelling of Earth Observation Satellite Images—Part 1
1 Introduction
2 State of the Art
3 Data Set Description
4 Active Learning
5 Semantic Labelling
6 Conclusions
References
8 AL4SLEO: An Active Learning Solution for the Semantic Labelling of Earth Observation Satellite Images—Part 2
1 Typical Examples
1.1 Semantic Multi-level Labelling
1.2 Semantic Multi-sensor Labelling
1.3 Semantic Multi-temporal Labelling
1.4 Conclusions
References
9 Deep Learning-Based Efficient Customer Segmentation for Online Retail Businesses
1 Introduction
2 Literature Review
3 Clustering Algorithms
3.1 K-Means Algorithm
3.2 K-Means++ algorithm
3.3 Evaluation Metrics
4 Dimensionality Reduction Algorithms
4.1 Principal Component Analysis (PCA)
4.2 AutoEncoders
5 Libraries
6 Proposed Approach
7 Conclusion
References
10 Optimization of Water Use in the Washing Process of Industrial Orange Juice Extractors for a Circular Economy Approach
1 Introduction
2 Methodology
2.1 Objective Function of this Research
3 Results
4 Discussion of Results
5 Conclusions
6 Future Research
References
11 Optimizing ROVs in Metaverse for Marine Oil Pipeline Maintenance Using Gorilla Troops Optimizer Algorithm
1 Introduction
2 Metaverse Environment Where the Project Is Implemented
3 Implementation of Gorillas Nature-Inspired Metaheuristics
4 GTO Algorithm with ROV System Datasets
5 Conclusions and Future Work
References
12 Parameter Identification of the Combined Battery Model Using Embedded PSO-GA
1 Introduction
2 Combined Battery Model
3 Evolutionary Method
3.1 Genetic Algorithm (GA)
3.2 Particle Swarm Optimization (PSO)
4 Embedded PSO-GA
5 Parameter Identification System
6 Results and Discussion
7 Conclusion
References
13 IoT Applied to Slowing the Effects on Pets Trapped in a Wildfire After a CONAGUA Alert Using an Intelligent Voice-Recognition Assistant
1 Introduction
2 Purpose
3 Theoretical Framework
3.1 IoT Definition
3.2 Wildfires
3.3 Principal Causes
3.4 Consequences and Conditions that Influence the Form and Speed at Which Fire Spreads
3.5 Related Research
4 How Are We Going to Retard the Fire
5 Methodology
5.1 Research Contribution
5.2 Novel Approach
6 System Assembly and Functionality
7 Components Needed to Assemble Our Intelligent Proposal
8 Results
8.1 Discussion of Results
9 Conclusion and Future Research
References