Anyong Qing is a Research Scientist with Temasek Laboratories at the National University of Singapore. He has been involved in various areas of research in electromagnetics and evolutionary computation, producing pioneering work in solving electromagnetic problems using evolutionary algorithms. Qing has authored 4 book chapters, 49 peer reviewed journal papers, and 37 conference presentations, and altogether has been cited by other researchers over 150 times. He was invited to contribute a review on electromagnetic inverse problems for the Wiley Encyclopedia of RF and Microwave Engineering. He is also an invited speaker for EuMW, IST, PIERS, etc. Qing received a Guest Professorship at Southwest Jiaotong University and was elected as a senior member of the IEEE in 2005. Qing holds a B.E from Tsinghua University and a PhD from Southwest Jiaotong.

• Preface. List of Figures.List of Tables.1 An Introduction to Optimization.1.1 A General Optimization Problem.1.2 Deterministic Optimization Algorithms.1.3 Stochastic Optimization Algorithms.1.4 Evolutionary Algorithms.References.2 Fundamentals of Differential Evolution.2.1 Differential Evolution at a Glimpse.2.2 Classic Differential Evolution.2.3 Intrinsic Control Parameters of Differential Evolution.2.4 Differential Evolution as an Evolutionary Algorithm.References.3 Advances in Differential Evolution.3.1 Handling Mixed Optimization Parameters.3.2 Advanced Differential Evolution Strategies.3.3 Multi-objective Differential Evolution.3.4 Parametric Study on Differential Evolution.3.5 Adaptation of Intrinsic Control Parameters of Differential Evolution.References.4 Configuring a Parametric Study on Differential Evolution.4.1 Motivations.4.2 Objectives.4.3 Scopes.4.4 Implementation Terminologies.4.5 Performance Indicators.4.6 Test Bed.4.7 Similar Works.4.8 A Comparative Study.5 Benchmarking a Single-Objective Optimization Test Bed for Parametric Study on Differential Evolution.5.1 Motivation.5.2 A Survey on Test Problems.5.3 Generating New Test Problems.5.4 Tentative Benchmark Test Bed.5.5 An Overview of Numerical Simulation.References.6 Differential Evolution Strategies.6.1 Sphere Function.6.2 Step Function 2.6.3 Hyper-ellipsoid Function.6.4 Qing Function.6.5 Schwefel Function 2.22.6.6 Schwefel Function 2.26.6.7 Schwefel Function 1.2.6.8 Rastrigin Function.6.9 Ackley Function.7 Optimal Intrinsic Control Parameters.7.1 Sphere Function.7.2 Step Function 2.7.3 Hyper-ellipsoid Function.7.4 Qing Function.7.5 Schwefel Function 2.22.7.6 Schwefel Function 2.26.7.7 Schwefel Function 1.2.7.8 Rastrigin Function.7.9 Ackley Function.8 Non-Intrinsic Control Parameters.8.1 Introduction.8.2 Alternative Search Space.8.3 Performance of Differential Evolution.8.4 Optimal Population Size and Safeguard Zone.8.5 Optimal Mutation Intensity and Crossover Probability for Sphere Function.9 An Introductory Survey on Differential Evolution in Electrical and Electronic Engineering.9.1 Communication.9.2 Computer Engineering.9.3 Control Theory and Engineering.9.4 Electrical Engineering.9.5 Electromagnetics.9.6 Electronics.9.7 Magnetics.9.8 Power Engineering.9.9 Signal and Information Processing.References.10 Flexible QoS Multicast Routing in Next-Generation Internet.10.1 Introduction.10.2 Mathematical Models.10.3 Performance Evaluation.10.4 Conclusions.10.5 Acknowledgement.References.11 Multisite Mapping onto Grid Environments.11.1 Introduction.11.2 Working Environment.11.3 Differential Evolution for Grid Mapping.11.4 Experiments in Predetermined Conditions.11.5 More Realistic Experiments.11.6 Conclusions.References.12 Synthesis of Time-Modulated Antenna Arrays.12.1 Introduction.12.2 Antenna Arrays.12.3 Synthesis of Multiple Patterns from Time-Modulated Arrays.12.4 Pattern Synthesis of Time-Modulated Planar Arrays.12.5 Adaptive Nulling with Time-Modulated Antenna Arrays.References.13 Automated Analog Electronic Circuits Sizing.13.1 Introduction.13.2 Cost Function.13.3 Hybrid Differential Evolution.13.4 Device Sizing.13.5 Conclusions.References.14 Strategic Bidding in a Competitive Electricity Market.14.1 Electrical Energy Market.14.2 Bidding Strategies in an Electricity Market.14.3 Application of Differential Evolution in Strategic Bidding Systems.14.4 Case Study.14.5 Conclusions.References.15 3D Tracking of License Plates in Video Sequences.15.1 Introduction.15.2 3D License Plate Tracking Acquisition Setup.15.3 Statistical Bayesian Estimation and Particle Filtering.15.4 3D License Plate Tracking Using DEMC Particle Filter.15.5 Comparison.15.6 Conclusions.References.16 Color Quantization.16.1 Introduction.16.2 Differential Evolution Based Color Map Generation.16.3 Hybrid Differential Evolution for Color Map Generation.16.4 Experimental Results.16.5 Conclusions.References.Index.

Anyong Qing is a Research Scientist with Temasek Laboratories at the National University of Singapore. He has been involved in various areas of research in electromagnetics and evolutionary computation, producing pioneering work in solving electromagnetic problems using evolutionary algorithms. Qing has authored 4 book chapters, 49 peer reviewed journal papers, and 37 conference presentations, and altogether has been cited by other researchers over 150 times. He was invited to contribute a review on electromagnetic inverse problems for the Wiley Encyclopedia of RF and Microwave Engineering. He is also an invited speaker for EuMW, IST, PIERS, etc. Qing received a Guest Professorship at Southwest Jiaotong University and was elected as a senior member of the IEEE in 2005. Qing holds a B.E from Tsinghua University and a PhD from Southwest Jiaotong.

• Preface. List of Figures.List of Tables.1 An Introduction to Optimization.1.1 A General Optimization Problem.1.2 Deterministic Optimization Algorithms.1.3 Stochastic Optimization Algorithms.1.4 Evolutionary Algorithms.References.2 Fundamentals of Differential Evolution.2.1 Differential Evolution at a Glimpse.2.2 Classic Differential Evolution.2.3 Intrinsic Control Parameters of Differential Evolution.2.4 Differential Evolution as an Evolutionary Algorithm.References.3 Advances in Differential Evolution.3.1 Handling Mixed Optimization Parameters.3.2 Advanced Differential Evolution Strategies.3.3 Multi-objective Differential Evolution.3.4 Parametric Study on Differential Evolution.3.5 Adaptation of Intrinsic Control Parameters of Differential Evolution.References.4 Configuring a Parametric Study on Differential Evolution.4.1 Motivations.4.2 Objectives.4.3 Scopes.4.4 Implementation Terminologies.4.5 Performance Indicators.4.6 Test Bed.4.7 Similar Works.4.8 A Comparative Study.5 Benchmarking a Single-Objective Optimization Test Bed for Parametric Study on Differential Evolution.5.1 Motivation.5.2 A Survey on Test Problems.5.3 Generating New Test Problems.5.4 Tentative Benchmark Test Bed.5.5 An Overview of Numerical Simulation.References.6 Differential Evolution Strategies.6.1 Sphere Function.6.2 Step Function 2.6.3 Hyper-ellipsoid Function.6.4 Qing Function.6.5 Schwefel Function 2.22.6.6 Schwefel Function 2.26.6.7 Schwefel Function 1.2.6.8 Rastrigin Function.6.9 Ackley Function.7 Optimal Intrinsic Control Parameters.7.1 Sphere Function.7.2 Step Function 2.7.3 Hyper-ellipsoid Function.7.4 Qing Function.7.5 Schwefel Function 2.22.7.6 Schwefel Function 2.26.7.7 Schwefel Function 1.2.7.8 Rastrigin Function.7.9 Ackley Function.8 Non-Intrinsic Control Parameters.8.1 Introduction.8.2 Alternative Search Space.8.3 Performance of Differential Evolution.8.4 Optimal Population Size and Safeguard Zone.8.5 Optimal Mutation Intensity and Crossover Probability for Sphere Function.9 An Introductory Survey on Differential Evolution in Electrical and Electronic Engineering.9.1 Communication.9.2 Computer Engineering.9.3 Control Theory and Engineering.9.4 Electrical Engineering.9.5 Electromagnetics.9.6 Electronics.9.7 Magnetics.9.8 Power Engineering.9.9 Signal and Information Processing.References.10 Flexible QoS Multicast Routing in Next-Generation Internet.10.1 Introduction.10.2 Mathematical Models.10.3 Performance Evaluation.10.4 Conclusions.10.5 Acknowledgement.References.11 Multisite Mapping onto Grid Environments.11.1 Introduction.11.2 Working Environment.11.3 Differential Evolution for Grid Mapping.11.4 Experiments in Predetermined Conditions.11.5 More Realistic Experiments.11.6 Conclusions.References.12 Synthesis of Time-Modulated Antenna Arrays.12.1 Introduction.12.2 Antenna Arrays.12.3 Synthesis of Multiple Patterns from Time-Modulated Arrays.12.4 Pattern Synthesis of Time-Modulated Planar Arrays.12.5 Adaptive Nulling with Time-Modulated Antenna Arrays.References.13 Automated Analog Electronic Circuits Sizing.13.1 Introduction.13.2 Cost Function.13.3 Hybrid Differential Evolution.13.4 Device Sizing.13.5 Conclusions.References.14 Strategic Bidding in a Competitive Electricity Market.14.1 Electrical Energy Market.14.2 Bidding Strategies in an Electricity Market.14.3 Application of Differential Evolution in Strategic Bidding Systems.14.4 Case Study.14.5 Conclusions.References.15 3D Tracking of License Plates in Video Sequences.15.1 Introduction.15.2 3D License Plate Tracking Acquisition Setup.15.3 Statistical Bayesian Estimation and Particle Filtering.15.4 3D License Plate Tracking Using DEMC Particle Filter.15.5 Comparison.15.6 Conclusions.References.16 Color Quantization.16.1 Introduction.16.2 Differential Evolution Based Color Map Generation.16.3 Hybrid Differential Evolution for Color Map Generation.16.4 Experimental Results.16.5 Conclusions.References.Index.

Anyong Qing is a Research Scientist with Temasek Laboratories at the National University of Singapore. He has been involved in various areas of research in electromagnetics and evolutionary computation, producing pioneering work in solving electromagnetic problems using evolutionary algorithms. Qing has authored 4 book chapters, 49 peer reviewed journal papers, and 37 conference presentations, and altogether has been cited by other researchers over 150 times. He was invited to contribute a review on electromagnetic inverse problems for the Wiley Encyclopedia of RF and Microwave Engineering. He is also an invited speaker for EuMW, IST, PIERS, etc. Qing received a Guest Professorship at Southwest Jiaotong University and was elected as a senior member of the IEEE in 2005. Qing holds a B.E from Tsinghua University and a PhD from Southwest Jiaotong.

• Preface. List of Figures.List of Tables.1 An Introduction to Optimization.1.1 A General Optimization Problem.1.2 Deterministic Optimization Algorithms.1.3 Stochastic Optimization Algorithms.1.4 Evolutionary Algorithms.References.2 Fundamentals of Differential Evolution.2.1 Differential Evolution at a Glimpse.2.2 Classic Differential Evolution.2.3 Intrinsic Control Parameters of Differential Evolution.2.4 Differential Evolution as an Evolutionary Algorithm.References.3 Advances in Differential Evolution.3.1 Handling Mixed Optimization Parameters.3.2 Advanced Differential Evolution Strategies.3.3 Multi-objective Differential Evolution.3.4 Parametric Study on Differential Evolution.3.5 Adaptation of Intrinsic Control Parameters of Differential Evolution.References.4 Configuring a Parametric Study on Differential Evolution.4.1 Motivations.4.2 Objectives.4.3 Scopes.4.4 Implementation Terminologies.4.5 Performance Indicators.4.6 Test Bed.4.7 Similar Works.4.8 A Comparative Study.5 Benchmarking a Single-Objective Optimization Test Bed for Parametric Study on Differential Evolution.5.1 Motivation.5.2 A Survey on Test Problems.5.3 Generating New Test Problems.5.4 Tentative Benchmark Test Bed.5.5 An Overview of Numerical Simulation.References.6 Differential Evolution Strategies.6.1 Sphere Function.6.2 Step Function 2.6.3 Hyper-ellipsoid Function.6.4 Qing Function.6.5 Schwefel Function 2.22.6.6 Schwefel Function 2.26.6.7 Schwefel Function 1.2.6.8 Rastrigin Function.6.9 Ackley Function.7 Optimal Intrinsic Control Parameters.7.1 Sphere Function.7.2 Step Function 2.7.3 Hyper-ellipsoid Function.7.4 Qing Function.7.5 Schwefel Function 2.22.7.6 Schwefel Function 2.26.7.7 Schwefel Function 1.2.7.8 Rastrigin Function.7.9 Ackley Function.8 Non-Intrinsic Control Parameters.8.1 Introduction.8.2 Alternative Search Space.8.3 Performance of Differential Evolution.8.4 Optimal Population Size and Safeguard Zone.8.5 Optimal Mutation Intensity and Crossover Probability for Sphere Function.9 An Introductory Survey on Differential Evolution in Electrical and Electronic Engineering.9.1 Communication.9.2 Computer Engineering.9.3 Control Theory and Engineering.9.4 Electrical Engineering.9.5 Electromagnetics.9.6 Electronics.9.7 Magnetics.9.8 Power Engineering.9.9 Signal and Information Processing.References.10 Flexible QoS Multicast Routing in Next-Generation Internet.10.1 Introduction.10.2 Mathematical Models.10.3 Performance Evaluation.10.4 Conclusions.10.5 Acknowledgement.References.11 Multisite Mapping onto Grid Environments.11.1 Introduction.11.2 Working Environment.11.3 Differential Evolution for Grid Mapping.11.4 Experiments in Predetermined Conditions.11.5 More Realistic Experiments.11.6 Conclusions.References.12 Synthesis of Time-Modulated Antenna Arrays.12.1 Introduction.12.2 Antenna Arrays.12.3 Synthesis of Multiple Patterns from Time-Modulated Arrays.12.4 Pattern Synthesis of Time-Modulated Planar Arrays.12.5 Adaptive Nulling with Time-Modulated Antenna Arrays.References.13 Automated Analog Electronic Circuits Sizing.13.1 Introduction.13.2 Cost Function.13.3 Hybrid Differential Evolution.13.4 Device Sizing.13.5 Conclusions.References.14 Strategic Bidding in a Competitive Electricity Market.14.1 Electrical Energy Market.14.2 Bidding Strategies in an Electricity Market.14.3 Application of Differential Evolution in Strategic Bidding Systems.14.4 Case Study.14.5 Conclusions.References.15 3D Tracking of License Plates in Video Sequences.15.1 Introduction.15.2 3D License Plate Tracking Acquisition Setup.15.3 Statistical Bayesian Estimation and Particle Filtering.15.4 3D License Plate Tracking Using DEMC Particle Filter.15.5 Comparison.15.6 Conclusions.References.16 Color Quantization.16.1 Introduction.16.2 Differential Evolution Based Color Map Generation.16.3 Hybrid Differential Evolution for Color Map Generation.16.4 Experimental Results.16.5 Conclusions.References.Index.