1st Edition

Computational Intelligence Paradigms for Optimization Problems Using MATLAB®/SIMULINK®

By S. Sumathi, L. Ashok Kumar, Surekha. P Copyright 2016
    623 Pages
    by CRC Press

    623 Pages 40 Color & 175 B/W Illustrations
    by CRC Press

    623 Pages 40 Color & 175 B/W Illustrations
    by CRC Press

    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.