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New Optimization Algorithms and their Applications
Atom-Based, Ecosystem-Based and Economics-Based
- 1st Edition - July 27, 2021
- Authors: Zhenxing Zhang, Liying Wang, Weiguo Zhao
- Language: English
- Paperback ISBN:9 7 8 - 0 - 3 2 3 - 9 0 9 4 1 - 9
- eBook ISBN:9 7 8 - 0 - 3 2 3 - 9 0 9 4 2 - 6
New Optimization Algorithms and Applications: Atom-Based, Ecosystem-Based and Economics-Based presents the development of three new optimization algorithms - an Atom Search Op… Read more
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Request a sales quoteNew Optimization Algorithms and Applications: Atom-Based, Ecosystem-Based and Economics-Based presents the development of three new optimization algorithms - an Atom Search Optimization (ASO) algorithm, an Artificial Ecosystem-Based Optimization algorithm (AEO), a Supply Demand Based Optimization (SDO), and their applications within engineering. These algorithms are based on benchmark functions and typical engineering cases. The book describes the algorithms in detail and demonstrates how to use them in engineering. The title verifies the performance of the algorithms presented, simulation results are given, and MATLAB® codes are provided for the methods described.
Over seven chapters, the book introduces ASO, AEO and SDO, and presents benchmark functions, engineering problems, and coding. This volume offers technicians and researchers engaged in computer and intelligent algorithm work and engineering with one source of information on novel optimization algorithms.
- Presents three novel optimization algorithms for engineering
- Gives various applications and design examples for each algorithm
- Provides simulation results to verify algorithm performance
- Includes MATLAB® codes for optimization methods
- Describes the mathematical models needed
Researchers and advanced students in engineering fields
Chapter 1 Introduction
1.1 Optimization Algorithms
1.2 A Short Survey of Optimization Algorithms
1.3 Organization of the Present Book
References
Chapter 2 Atom Search Optimization Algorithm
2.1. Introduction
2.2 Basic Molecular Dynamics
2.3 Atom Search Optimization (ASO)
2.3.1 Mathematical Representation of Interaction Force
2.3.2 Mathematical Representation of Geometric Constraint
2.3.3 Mathematical Representation of Atomic Motion
2.3.4 Framework of ASO Algorithm
2.4 Experimental Results
2.4.1 Benchmark Functions
2.4.2 Experimental Setup
2.4.3 Results and Discussion
2.5 Conclusions
References
Chapter 3 Engineering Applications of Atom Search Optimization Algorithm
3.1 Introduction
3.2 Parameter Estimation for Chaotic System
3.2.1 Simulation Model
3.2.2 Results and Discussion
3.3 Circular Antenna Array Design Problem
3.3.1 Problem Description
3.3.2 Results and Discussion
3.4 Spread Spectrum Radar Polly Phase Code Design
3.4.1 Problem Description
3.4.2 Results and Discussion
3.5 Conclusions
References
Chapter 4 Artificial Ecosystem-based Optimization Algorithm
4.1 Introduction
4.2 Artificial Ecosystem-based Optimization (AEO)
4.2.1 Inspiration
4.2.2 Artificial Ecosystem-Based Optimization
4.3 Results and Discussion
4.3.1 Analysis of Exploitation Capability
4.3.2 Analysis of Exploration Capability
4.3.3 Analysis of Avoidance of Local Optima
4.3.4 Analysis of Convergence Behavior
4.3.5 Statistical Significance Analysis
4.3.6 Sensitivity Analysis
4.4 Conclusions
References
Chapter 5 Engineering Applications of Artificial Ecosystem-Based Optimization Algorithm
5.1 Engineering Optimization Using AEO Algorithm
5.1.1 Tension/Compression Spring Design
5.1.2 Pressure Vessel Design
5.1.3 Welded Beam Design
5.1.4 Speed Reducer Design
5.1.5 Multiple Disc Clutch Brake Design
5.2 Static Economic Load Dispatch (ELD) Problem
5.2.1 Problem Description
5.2.2 Results and Discussion
5.3 Hydrothermal Scheduling Problem
5.3.1 Problem Description
5.3.2 Results and Discussion
5.4 Conclusions
References
Chapter 6 Supply-Demand-based Optimization
6.1 Introduction
6.2 Supply-Demand-Based Optimization (SDO)
6.2.1 Inspiration
6.2.2 Supply-Demand-Based Optimization (SDO)
6.3 Experimental Results and Discussion
6.3.1 Experimental Setup
6.3.2 Analysis of Exploitation Capability
6.3.3 Analysis of Exploration Capability
6.3.4 Analysis of Avoidance of Local Optima
6.3.5 Analysis of Convergence Behavior
6.4 Conclusions
References
Chapter 7 Engineering Applications of Supply-Demand-based Optimization
7.1 Three-Bar Truss Design
7.2 Cantilever Beam Design
7.3 Rolling Element Bearing Design
7.4 Gear Train Design
7.5 Conclusions
References
Appendix
Appendix A: Benchmark Functions
Appendix B: Engineering Design Problems
Appendix C: Codes in MATLAB
- No. of pages: 178
- Language: English
- Edition: 1
- Published: July 27, 2021
- Imprint: Elsevier
- Paperback ISBN: 9780323909419
- eBook ISBN: 9780323909426
ZZ
Zhenxing Zhang
Dr. Zhenxing Zhang is a Hydrologist, at the University of Illinois at Urbana-Champaign, USA. His research focuses on surface water supply, water availability, hydrologic modelling, and stochastic hydrology.
Affiliations and expertise
Hydrologist, University of Illinois at Urbana-Champaign, USA.LW
Liying Wang
Liying Wang is a Professor in the School of Water Conservancy and Hydroelectric Power, at Hebei university of Engineering, in China. His research focuses on intelligent computing, hydromechanical dynamics, and water resources for optimal allocation.
Affiliations and expertise
Professor, School of Water Conservancy and Hydroelectric Power, Hebei university of Engineering, ChinaWZ
Weiguo Zhao
Weiguo Zhao is Associate Professor in the School of Water Conservancy and Hydroelectric Power, at Hebei University of Engineering, in China. His research focuses on intelligent computing, intelligent fault diagnosis, and smart water conservancy.
Affiliations and expertise
Associate Professor, School of Water Conservancy and Hydroelectric Power, Hebei University of Engineering, ChinaRead New Optimization Algorithms and their Applications on ScienceDirect