Optimization Techniques in Engineering. Advances and Applications

Cover
Title Page
Copyright Page
Contents
Preface
Acknowledgment
Part 1: Soft Computing and Evolutionary-Based Optimization
	Chapter 1 Improved Grey Wolf Optimizer with Levy Flight to Solve Dynamic Economic Dispatch Problem with Electric Vehicle Profiles
		1.1 Introduction
		1.2 Problem Formulation
			1.2.1 Power Output Limits
			1.2.2 Power Balance Limits
			1.2.3 Ramp Rate Limits
			1.2.4 Electric Vehicles
		1.3 Proposed Algorithm
			1.3.1 Overview of Grey Wolf Optimizer
			1.3.2 Improved Grey Wolf Optimizer with Levy Flight
			1.3.3 Modeling of Prey Position with Levy Flight Distribution
		1.4 Simulation and Results
			1.4.1 Performance of Improved GWOLF on Benchmark Functions
			1.4.2 Performance of Improved GWOLF for Solving DED for the Different Charging Probability Distribution
		1.5 Conclusion
		References
	Chapter 2 Comparison of YOLO and Faster R-CNN on Garbage Detection
		2.1 Introduction
		2.2 Garbage Detection
			2.2.1 Transfer Learning-Technique
			2.2.2 Inception-Custom Model
		2.3 Experimental Results
			2.3.1 Results Obtained Using YOLO Algorithm
			2.3.2 Results Obtained Using Faster R-CNN
		2.4 Future Scope
		2.5 Conclusion
		References
	Chapter 3 Smart Power Factor Correction and Energy Monitoring System
		3.1 Introduction
		3.2 Block Diagram
			3.2.1 Power Factor Concept
			3.2.2 Power Factor Calculation
		3.3 Simulation
		3.4 Conclusion
		References
	Chapter 4 ANN-Based Maximum Power Point Tracking Control Configured Boost Converter for Electric Vehicle Applications
		4.1 Introduction
		4.2 Block Diagram
		4.3 ANN-Based MPPT for Boost Converter
		4.4 Closed Loop Control
		4.5 Simulation Results
		4.6 Conclusion
		References
	Chapter 5 Single/Multijunction Solar Cell Model Incorporating Maximum Power Point Tracking Scheme Based on Fuzzy Logic Algorithm
		5.1 Introduction
		5.2 Modeling Structure
			5.2.1 Single-Junction Solar Cell Model
			5.2.2 Modeling of Multijunction Solar PV Cell
		5.3 MPPT Design Techniques
			5.3.1 Design of MPPT Scheme Based on P&O Technique
			5.3.2 Design of MPPT Scheme Based on FLA
		5.4 Results and Discussions
			5.4.1 Single-Junction Solar Cell
			5.4.2 Multijunction Solar PV Cell
			5.4.3 Implementation of MPPT Scheme Based on P&O Technique
			5.4.4 Implementation of MPPT Scheme Based on FLA
		5.5 Conclusion
		References
	Chapter 6 Particle Swarm Optimization: An Overview, Advancements and Hybridization
		6.1 Introduction
		6.2 The Particle Swarm Optimization: An Overview
		6.3 PSO Algorithms and Pseudo-Code
			6.3.1 PSO Algorithm
			6.3.2 Pseudo-Code for PSO
			6.3.3 PSO Limitations
		6.4 Advancements in PSO and Its Perspectives
			6.4.1 Inertia Weight
			6.4.2 Constriction Factors
			6.4.3 Topologies
			6.4.4 Analysis of Convergence
		6.5 Hybridization of PSO
			6.5.1 PSO Hybridization with Artificial Bee Colony (ABC)
			6.5.2 PSO Hybridization with Ant Colony Optimization (ACO)
			6.5.3 PSO Hybridization with Genetic Algorithms (GA)
		6.6 Area of Applications of PSO
		6.7 Conclusions
		References
	Chapter 7 Application of Genetic Algorithm in Sensor Networks and Smart Grid
		7.1 Introduction
		7.2 Communication Sector
			7.2.1 Sensor Networks
		7.3 Electrical Sector
			7.3.1 Smart Microgrid
		7.4 A Brief Outline of GAs
		7.5 Sensor Network’s Energy Optimization
		7.6 Sensor Network’s Coverage and Uniformity Optimization Using GA
		7.7 Use GA for Optimization of Reliability and Availability for Smart Microgrid
		7.8 GA Versus Traditional Methods
		7.9 Summaries and Conclusions
		References
	Chapter 8 AI-Based Predictive Modeling of Delamination Factor for Carbon Fiber–Reinforced Polymer (CFRP) Drilling Process
		8.1 Introduction
		8.2 Methodology
		8.3 AI-Based Predictive Modeling
			8.3.1 Linear Regression
			8.3.2 Random Forests
			8.3.3 XGBoost
			8.3.4 SVM
		8.4 Performance Indices
			8.4.1 Root Mean Squared Error (RMSE)
			8.4.2 Mean Squared Error (MSE)
			8.4.3 R2 (R-Squared)
		8.5 Results and Discussion
			8.5.1 Key Performance Metrics (KPIs) During the Model Training Phase
			8.5.2 Key Performance Index Metrics (KPIs) During the Model Testing Phase
			8.5.3 K Cross Fold Validation
		8.6 Conclusions
		References
	Chapter 9 Performance Comparison of Differential Evolutionary Algorithm-Based Contour Detection to Monocular Depth Estimation for Elevation Classification in 2D Drone-Based Imagery
		9.1 Introduction
		9.2 Literature Survey
		9.3 Research Methodology
			9.3.1 Dataset and Metrics
		9.4 Result and Discussion
		9.5 Conclusion
		References
	Chapter 10 Bioinspired MOPSO-Based Power Allocation for Energy Efficiency and Spectral Efficiency Trade-Off in Downlink NOMA
		10.1 Introduction
		10.2 System Model
		10.3 User Clustering
		10.4 Optimal Power Allocation for EE-SE Tradeoff
			10.4.1 Multiobjective Optimization Problem
			10.4.2 Multiobjective PSO
			10.4.3 MOPSO Algorithm for EE-SE Trade-Off in Downlink NOMA
		10.5 Numerical Results
		10.6 Conclusion
		References
	Chapter 11 Performances of Machine Learning Models and Featurization Techniques on Amazon Fine Food Reviews
		11.1 Introduction
			11.1.1 Related Work
		11.2 Materials and Methods
			11.2.1 Data Cleaning and Pre-Processing
			11.2.2 Feature Extraction
			11.2.3 Classifiers
		11.3 Results and Experiments
		11.4 Conclusion
		References
	Chapter 12 Optimization of Cutting Parameters for Turning by Using Genetic Algorithm
		12.1 Introduction
		12.2 Genetic Algorithm GA: An Evolutionary Computational Technique
		12.3 Design of Multiobjective Optimization Problem
			12.3.1 Decision Variables
			12.3.2 Objective Functions
			12.3.3 Bounds of Decision Variables
			12.3.4 Response Variables
		12.4 Results and Discussions
			12.4.1 Single Objective Optimization
			12.4.2 Results of Multiobjective Optimization
		12.5 Conclusion
		References
	Chapter 13 Genetic Algorithm-Based Optimization for Speech Processing Applications
		13.1 Introduction to GA
			13.1.1 Enhanced GA
		13.2 GA in Automatic Speech Recognition
			13.2.1 GA for Optimizing Off-Line Parameters in Voice Activity Detection (VAD)
			13.2.2 Classification of Features in ASR Using GA
			13.2.3 GA-Based Distinctive Phonetic Features Recognition
			13.2.4 GA in Phonetic Decoding
		13.3 Genetic Algorithm in Speech Emotion Recognition
			13.3.1 Speech Emotion Recognition
			13.3.2 Genetic Algorithms in Speech Emotion Recognition
		13.4 Genetic Programming in Hate Speech Using Deep Learning
			13.4.1 Introduction to Hate Speech Detection
			13.4.2 GA Integrated With Deep Learning Models for Hate Speech Detection
		13.5 Conclusion
		References
	Chapter 14 Performance of P, PI, PID, and NARMA Controllers in the Load Frequency Control of a Single-Area Thermal Power Plant
		14.1 Introduction
		14.2 Single-Area Power System
		14.3 Automatic Load Frequency Control (ALFC)
		14.4 Controllers Used in the Simulink Model
			14.4.1 PID Controller
			14.4.2 PI Controller
			14.4.3 P Controller
		14.5 Circuit Description
		14.6 ANN and NARMA L2 Controller
		14.7 Simulation Results and Comparative Analysis
		14.8 Conclusion
		References
Part 2: Decision Science and Simulation-Based Optimization
	Chapter 15 Selection of Nonpowered Industrial Truck for Small Scale Manufacturing Industry Using Fuzzy VIKOR Method Under FMCDM Environment
		15.1 Introduction
		15.2 Fuzzy Set Theory
			15.2.1 Some Important Fuzzy Definitions
			15.2.2 Fuzzy Operations
			15.2.3 Linguistic Variable (LV)
		15.3 FVIKOR
		15.4 Problem Definition
		15.5 Results and Discussions
		15.6 Conclusions
		References
	Chapter 16 Slightly and Almost Neutrosophic gsα*—Continuous Function in Neutrosophic Topological Spaces
		16.1 Introduction
		16.2 Preliminaries
		16.3 Slightly Neutrosophic gsα* – Continuous Function
		16.4 Almost Neutrosophic gsα* – Continuous Function
		16.5 Conclusion
		References
	Chapter 17 Identification and Prioritization of Risk Factors Affecting the Mental Health of Farmers
		17.1 Introduction
		17.2 Materials and Methods
		17.2.1 ELECTRE Technique
		17.3 Result and Discussion
		17.4 Conclusion
		References
	Chapter 18 Multiple Objective and Subjective Criteria Evaluation Technique (MOSCET): An Application to Material Handling System Selection
		18.1 Introduction
		18.2 Multiple Objective and Subjective Criteria Evaluation Technique (MOSCET): The Proposed Algorithm
		18.3 Illustrative Example
			18.3.1 Problem Definition
			18.3.2 Calculation and Discussions
		18.4 Conclusions
		References
	Chapter 19 Evaluation of Optimal Parameters to Enhance Worker’s Performance in an Automotive Industry
		19.1 Introduction
		19.2 Methodology
		19.3 Results and Discussion
		19.4 Conclusions
		References
	Chapter 20 Determining Key Influential Factors of Rural Tourism—An AHP Model
		20.1 Introduction
		20.2 Rural Tourism
		20.3 Literature Review
		20.4 Objectives
		20.5 Methodology
		20.6 Analysis
		20.7 Results and Discussion
		20.8 Conclusions
		20.9 Managerial Implications
		References
	Chapter 21 Solution of a Pollution-Based Economic Order Quantity Model Under Triangular Dense Fuzzy Environment
		21.1 Introduction
			21.1.1 Overview
			21.1.2 Motivation and Specific Study
		21.2 Preliminaries
			21.2.1 Pollution Function
			21.2.2 Triangular Dense Fuzzy Set (TDFS)
		21.3 Notations and Assumptions
			21.3.1 Case Study
		21.4 Formulation of the Mathematical Model
			21.4.1 Crisp Mathematical Model
			21.4.2 Formulation of Triangular Dense Fuzzy Mathematical Model
			21.4.3 Defuzzification of Triangular Dense Fuzzy Model
		21.5 Numerical Illustration
		21.6 Sensitivity Analysis
		21.7 Graphical Illustration
		21.8 Merits and Demerits
		21.9 Conclusion
		Acknowledgement
		Appendix
		References
	Chapter 22 Common Yet Overlooked Aspects Accountable for Antiaging: An MCDM Approach
		22.1 Introduction
		22.2 Literature Review
		22.3 Analytic Hierarchy Process (AHP)
		22.4 Result and Discussion
		22.5 Conclusion
		References
	Chapter 23 E-Waste Management Challenges in India: An AHP Approach
		23.1 Introduction
		23.2 Literature Review
		23.3 Methodology
		23.4 Results and Discussion
		23.5 Conclusion
		References
	Chapter 24 Application of k-Means Method for Finding Varying Groups of Primary Energy Household Emissions in the Indian States
		24.1 Introduction
		24.2 Literature Review
		24.3 Materials and Methods
			24.3.1 Data Preparation
			24.3.2 Methods and Approach
		24.4 Exploratory Data Analysis
		24.5 Results and Discussion
		24.6 Conclusion
		References
	Chapter 25 Airwaves Detection and Elimination Using Fast Fourier Transform to Enhance Detection of Hydrocarbon
		25.1 Introduction
			25.1.1 Airwaves
			25.1.2 Fast Fourier Transform
		25.2 Related Works
		25.3 Theoretical Framework
		25.4 Methodology
		25.5 Results and Discussions
		25.6 Conclusion
		References
	Chapter 26 Design and Implementation of Control for Nonlinear Active Suspension System
		26.1 Introduction
		26.2 Mathematical Model of Quarter Car Suspension System
			26.2.1 Mathematical Model
			26.2.2 Linearization Method for Nonlinear System Model
			26.2.3 Discussion of Result
		26.3 Conclusion
		References
	Chapter 27 A Study of Various Peak to Average Power Ratio (PAPR) Reduction Techniques for 5G Communication System (5G-CS)
		27.1 Introduction
		27.2 Literature Review
		27.3 Overview of 5G Cellular System
		27.4 PAPR
			27.4.1 Continuous Time PAPR
			27.4.2 Continuous Time PAPR
		27.5 Factors on which PAPR Reduction Depends
		27.6 PAPR Reduction Technique
			27.6.1 Scrambling of Signals
			27.6.2 Signal Distortion Technique
			27.6.3 High Power Amplifier (HPA)
		27.7 Limitation of OFDM
		27.8 Universal Filter Multicarrier (UMFC) Emerging Technique to Reduce PAPR in 5G
			27.8.1 Transmitter of UMFC
			27.8.2 Receiver of UMFC
		27.9 Comparison Between Various Techniques
		27.10 Conclusion
		References
	Chapter 28 Investigation of Rebound Suppression Phenomenon in an Electromagnetic V-Bending Test
		28.1 Introduction
		28.2 Investigation
			28.2.1 Specimen for Tests
			28.2.2 Design of Die and Tool
			28.2.3 Configuration and Procedure
		28.3 Mathematical Evaluation
			28.3.1 Simulation Methodology
		28.4 Modeling for Material
			28.4.1 Suppressing Rebound Phenomenon
		28.5 Conclusion
		References
	Chapter 29 Quadratic Spline Function Companding Technique to Minimize Peak-to-Average Power Ratio in Orthogonal Frequency Division Multiplexing System
		29.1 Introduction
		29.2 OFDM System
			29.2.1 PAPR of OFDM Signal
		29.3 Companding Technique
			29.3.1 Quadratic Spline Function Companding
		29.4 Numerical Results and Discussion
		29.5 Conclusion
		Acknowledgment
		References
	Chapter 30 A Novel MCGDM Approach for Supplier Selection in a Supply Chain Management
		30.1 Introduction
		30.2 Proposed Algorithm
		30.3 Illustrative Example
			30.3.1 Problem Definition
			30.3.2 Calculation and Discussions
		30.4 Conclusions
		References
Index
EULA