1st Edition
Computational Intelligence Paradigms for Optimization Problems Using MATLAB®/SIMULINK®
Considered one of the most innovative research directions, computational intelligence (CI) embraces techniques that use global search optimization, machine learning, approximate reasoning, and connectionist systems to develop efficient, robust, and easy-to-use solutions amidst multiple decision variables, complex constraints, and tumultuous environments. CI techniques involve a combination of learning, adaptation, and evolution used for intelligent applications.
Computational Intelligence Paradigms for Optimization Problems Using MATLAB®/ Simulink® explores the performance of CI in terms of knowledge representation, adaptability, optimality, and processing speed for different real-world optimization problems.
Focusing on the practical implementation of CI techniques, this book:
- Discusses the role of CI paradigms in engineering applications such as unit commitment and economic load dispatch, harmonic reduction, load frequency control and automatic voltage regulation, job shop scheduling, multidepot vehicle routing, and digital image watermarking
- Explains the impact of CI on power systems, control systems, industrial automation, and image processing through the above-mentioned applications
- Shows how to apply CI algorithms to constraint-based optimization problems using MATLAB® m-files and Simulink® models
- Includes experimental analyses and results of test systems
Computational Intelligence Paradigms for Optimization Problems Using MATLAB®/ Simulink® provides a valuable reference for industry professionals and advanced undergraduate, postgraduate, and research students.
Introduction
Learning Objectives
Computational Intelligence Paradigms
Classification of Computational Intelligence Algorithms
Role of CI Paradigms in Engineering Applications
Applications of CI Focused in This Book
Summary
References
Unit Commitment and Economic Load Dispatch Problem
Learning Objectives
Introduction
Economic Operation of Power Generation
Mathematical Model of the UC-ELD Problem
Intelligent Algorithms for Solving UC-ELD
MATLAB® m-File Snippets for UC-ELD Based on CI Paradigms
Discussion
Advantages of CI Algorithms
Summary
References
Harmonic Reduction in Power Systems
Learning Objectives
Harmonic Reduction in Power System
Harmonic Effects
Harmonics Limits and Standards
Method to Eliminate Harmonics
Voltage Source Inverter-Fed Induction Motor Drives
Case Study: Pulp and Paper Industry
Genetic Algorithm-Based Filter Design in 2-, 6-, and 12-Pulse Rectifier
Bacterial Foraging Algorithm for Harmonic Elimination
Summary
References
Voltage and Frequency Control in Power Systems
Learning Objectives
Introduction
Scope of Intelligent Algorithms in Voltage and Frequency Control
Dynamics of Power Generating System
Fuzzy Logic Controller for LFC and AVR
Genetic Algorithm for LFC and AVR
PSO and ACO for LFC and AVR
Hybrid Evolutionary Algorithms for LFC and AVR
Summary
References
Job Shop Scheduling Problem
Learning Objectives
Introduction
Formulation of JSSP
Computational Intelligence Paradigms for JSSP
m-File Snippets and Outcome of JSSP Based on CI Paradigms
Discussion
Advantages of CI Paradigms
Summary
References
Multidepot Vehicle Routing Problem
Learning Objectives
Introduction
Fundamental Concepts of MDVRP
Computational Intelligence Algorithms for MDVRP
MATLAB® m-File Snippets for MDVRP Based on CI Paradigms
Discussions
Advantages of CI Paradigms
Summary
References
Digital Image Watermarking
Learning Objectives
Introduction
Basic Concepts of Image Watermarking
Preprocessing Schemes
Discrete Wavelet Transform for DIWM
Performance Metrics
Application of CI Techniques for DIWM
MATLAB® m-File Snippets for DIWM Using CI Paradigms
Optimization in Watermarking
Discussion
Advantages of CI Paradigms
Summary
References
Appendix A: Unit Commitment and Economic Load Dispatch Test Systems
Appendix B: Harmonic Reduction—MATLAB®/Simulink® Models
Appendix C: MATLAB®/Simulink® Functions—An Overview
Appendix D: Instances of Job-Shop Scheduling Problems
Appendix E: MDVRP Instances
Appendix F: Image Watermarking Metrics and Attacks
Biography
S. Sumathi completed her BE in Electronics and Communication Engineering and her ME in Applied Electronics at the Government College of Technology, Coimbatore. She earned her PhD in the area of Data Mining and is an Associate Professor in the Department of Electrical and Electronics Engineering at PSG College of Technology, Coimbatore. Widely published and highly decorated, Dr. Sumathi has 25 years of teaching and research experience. Her research interests include neural networks, fuzzy systems and genetic algorithms, pattern recognition and classification, data warehousing and data mining, and operating systems and parallel computing.
L. Ashok Kumar completed his graduate program in Electrical and Electronics Engineering, his postgraduate studies with an Electrical Machines major, his MBA with a specialization in Human Resource Development, and his PhD in Wearable Electronics. He was previously a project engineer at ITC Limited, Paperboards and Specialty Papers Division, Kovai Unit, Coimbatore. Widely published and highly decorated, Dr. Ashok is currently a Professor in the Department of Electrical and Electronics Engineering at PSG College of Technology, Coimbatore. His research areas include wearable electronics, solar PV and wind energy systems, textile control engineering, smart grid, energy conservation and management, and power electronics and drives.
Surekha P. completed her BE in Electrical and Electronics Engineering at PARK College of Engineering and Technology, Coimbatore, and her master’s degree in Control Systems at PSG College of Technology, Coimbatore. She earned her PhD in Computational Intelligence for Electrical Engineering Applications at Anna University, Chennai. Widely published and highly decorated, Dr. Surekha P. is an Associate Professor in the Department of Electrical and Electronics Engineering at PES University, Bangalore. A member of several technical bodies, she is a popular reviewer of journal and IEEE-sponsored conference publications. Her areas of research include robotics, virtual instrumentation, control systems, smart grid, evolutionary algorithms, and computational intelligence.