Sumathi S., Kumar L.A., Surekha P. Computational Intelligence Paradigms for Optimization Problems Using MatLAB/Simulink

Springer, 2016. — 615 p.Solutions to constraint-based optimization problems using CI paradigms with MATLABR m-files and SimulinkR models are chosen as the pedestal for this book. This book is written in an attempt to explore the performance of CI in terms of knowledge representation, adaptability, optimality, and processing speed for different real-world problems. This book covers CI paradigms and their role in different 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. The impact of CI algorithms in the area of power systems, control systems, industrial automation, and image processing is explained with practical implementation using MatLAB/Simulink. Each application is presented with an implementation of CI algorithm, methodology to apply CI algorithms to the problem under consideration, solution approach using MatLAB/Simulink, and an extensive analysis with problem-dependent test data.
A detailed explanation is included for all the topics with the intention that engineers and scientists can benefit from preliminaries on the subject from both application and research points of view. This book is intended for higher-level undergraduate, postgraduate, and research students interested in understanding and implementing CI algorithms for various applications based on MatLAB/Simulink.Unit Commitment and Economic Load Dispatch Problem
Harmonic Reduction in Power Systems
Voltage and Frequency Control in Power Systems
Job Shop Scheduling Problem
Multidepot Vehicle Routing Problem
Digital Image WatermarkingA: Unit Commitment and Economic Load Dispatch Test Systems
B: Harmonic Reduction—MatLAB/Simulink Models
C: MatLAB/Simulink Functions—An Overview
D: Instances of Job-Shop Scheduling Problems
E: MDVRP Instances
F: Image Watermarking Metrics and Attacks