Preface |
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vii | |
About the Authors |
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ix | |
Acknowledgments |
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xi | |
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1 | (8) |
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2 Simulation-Driven Antenna Design |
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9 | (18) |
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2.1 Simulation-Driven Design of Antenna Structures |
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9 | (7) |
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16 | (8) |
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2.3 Challenges of Contemporary Antenna Design |
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24 | (3) |
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3 Introduction to Numerical Optimization |
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27 | (20) |
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3.1 Optimization Problem Formulation |
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28 | (1) |
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3.2 Gradient-Based Optimization Techniques |
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29 | (11) |
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3.2.1 Gradient-Based Optimization Using Descent Methods |
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30 | (3) |
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3.2.2 Newton and Quasi-Newton Methods |
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33 | (3) |
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3.2.3 Remarks on Constrained Optimization |
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36 | (4) |
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3.3 Derivative-Free Optimization |
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40 | (5) |
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41 | (1) |
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3.3.2 Nelder-Mead Algorithm |
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42 | (3) |
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45 | (2) |
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4 Global Optimization Using Population-Based Metaheuristics |
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47 | (20) |
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4.1 Introduction to Population-Based Metaheuristics |
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48 | (3) |
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51 | (3) |
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54 | (5) |
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4.3.1 Algorithm Structure and Representation |
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54 | (1) |
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54 | (2) |
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56 | (1) |
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56 | (1) |
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57 | (1) |
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58 | (1) |
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4.4 Evolutionary Algorithms |
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59 | (1) |
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4.5 Particle Swarm Optimization |
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60 | (2) |
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4.6 Differential Evolution |
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62 | (2) |
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64 | (1) |
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64 | (3) |
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5 Surrogate-Based Modeling and Optimization |
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67 | (34) |
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5.1 Surrogate-Based Optimization: Brief Introduction |
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67 | (4) |
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5.2 Surrogate Modeling: Data-Driven Surrogates |
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71 | (10) |
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5.2.1 Surrogate Modeling Flow |
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72 | (1) |
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5.2.2 Design of Experiments |
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73 | (1) |
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5.2.3 Data-Driven Modeling Techniques |
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74 | (6) |
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80 | (1) |
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5.3 Surrogate Modeling: Physics-Based Surrogates |
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81 | (5) |
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5.4 Optimization Using Data-Driven Surrogates |
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86 | (5) |
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5.4.1 Optimization Using Response Surfaces |
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86 | (2) |
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5.4.2 Sequential Approximate Optimization |
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88 | (1) |
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5.4.3 Optimization with Kriging Surrogates: Exploration versus Exploitation |
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89 | (2) |
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91 | (1) |
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5.5 Surrogate-Based Optimization Using Physics-Based Surrogates |
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91 | (10) |
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91 | (3) |
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5.5.2 Approximation Model Management Optimization |
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94 | (1) |
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95 | (1) |
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5.5.4 Shape Preserving Response Prediction |
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95 | (2) |
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5.5.5 Adaptively Adjusted Design Specifications |
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97 | (3) |
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100 | (1) |
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6 Multi-Objective Optimization |
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101 | (20) |
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6.1 Formulation of Multi-Objective Optimization Problem |
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102 | (1) |
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103 | (3) |
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106 | (1) |
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6.4 Goal Attainment Method |
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107 | (1) |
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6.5 Multi-Objective Evolutionary Algorithms |
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108 | (8) |
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6.5.1 Algorithm Structure and Search Mechanisms |
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109 | (1) |
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6.5.2 Assessment of Individuals |
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110 | (1) |
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110 | (2) |
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112 | (1) |
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113 | (1) |
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6.5.6 Mating Restrictions |
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114 | (1) |
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115 | (1) |
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6.6 Other Multi-Objective Metaheuristics |
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116 | (2) |
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6.6.1 Multi-Objective Particle Swarm Optimization |
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116 | (1) |
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6.6.2 Multi-Objective Differential Evolution |
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117 | (1) |
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118 | (3) |
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7 Multi-Objective Antenna Optimization Using Surrogate Models |
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121 | (20) |
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7.1 Optimization Using Response Surface Approximation Surrogates and Pareto Front Refinement |
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122 | (7) |
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7.1.1 Kriging and Co-Kriging Interpolation |
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123 | (2) |
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7.1.2 Construction of the Response Surface Approximation Surrogate: Obtaining Initial Pareto Set |
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125 | (2) |
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7.1.3 Pareto Set Refinement Using Response Correction |
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127 | (1) |
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7.1.4 Pareto Set Refinement Using Co-Kriging |
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128 | (1) |
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7.1.5 Optimization Flow Summary |
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128 | (1) |
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7.2 Optimization by Means of Pareto Front Exploration |
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129 | (5) |
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7.2.1 Optimization Algorithm |
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129 | (1) |
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7.2.2 Pareto Front Exploration Using Local Response Surface Approximation Models |
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130 | (3) |
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133 | (1) |
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7.2.4 Alternative Exploration Methods |
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134 | (1) |
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7.3 Optimization Using Sequential Domain Patching |
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134 | (5) |
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135 | (1) |
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7.3.2 Sequential Domain Patching Algorithm |
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136 | (1) |
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7.3.3 Automated Determination of Patch Sizes |
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137 | (1) |
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7.3.4 Pareto Set Refinement |
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138 | (1) |
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139 | (2) |
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8 Design Space Reduction Methods |
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141 | (14) |
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8.1 Design Space Reduction for Antenna Design |
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142 | (2) |
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8.2 Space Reduction Using Extreme Pareto-Optimal Designs |
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144 | (1) |
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8.3 Rotational Design Space Reduction Algorithm |
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145 | (4) |
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8.4 Design Space Confinement |
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149 | (2) |
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151 | (4) |
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9 Multi-Objective Optimization of Antenna Structures: Application Case Studies |
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155 | (70) |
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9.1 Design of Planar Yagi Antenna Using Decomposition |
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156 | (7) |
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9.1.1 Antenna Geometry and Electromagnetic Models |
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156 | (2) |
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158 | (2) |
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160 | (3) |
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9.2 Design of Ultra-Wideband Monopole Antenna Using Multi-Objective Evolutionary Algorithm and Co-Kriging |
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163 | (2) |
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9.2.1 Antenna Geometry and Design Objectives |
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163 | (1) |
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9.2.2 Electromagnetic Models Setup |
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164 | (1) |
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164 | (1) |
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9.3 Optimization of Dielectric Resonator Antenna Using Design Space Reduction and Multi-Objective Evolutionary Algorithm |
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165 | (12) |
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167 | (1) |
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9.3.2 Design Objectives and Antenna Models |
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168 | (1) |
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9.3.3 Design Space Reduction and Surrogate Model Construction |
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169 | (2) |
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171 | (2) |
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9.3.5 Multi-Objective Optimization in Initially Reduced Space |
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173 | (4) |
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177 | (1) |
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9.4 Design of a 12-Variable Yagi Antenna Using Design Space Reduction and Multi-Objective Evolutionary Algorithm |
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177 | (7) |
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9.4.1 Antenna Description and Design Objectives |
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178 | (1) |
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9.4.2 Antenna Models and Design Space Reduction |
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179 | (1) |
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179 | (3) |
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182 | (2) |
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9.5 Design of a Monopole Antenna Using Sequential Domain Patching |
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184 | (6) |
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9.5.1 Antenna Description and Design Objectives |
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184 | (1) |
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9.5.2 Antenna Models and Determination of Extreme Pareto Designs |
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185 | (1) |
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9.5.3 Multi-Objective Optimization Using Sequential Domain Patching Algorithm |
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186 | (3) |
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9.5.4 Comparison with Benchmark Techniques |
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189 | (1) |
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9.6 Optimization of Compact Monopole Antenna by Means of Pareto Front Exploration |
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190 | (9) |
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9.6.1 Antenna Description and Design Objectives |
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190 | (1) |
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9.6.2 Antenna Models and Initial Design |
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191 | (1) |
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192 | (3) |
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9.6.4 Comparison with Benchmark Techniques |
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195 | (2) |
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197 | (2) |
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9.7 Design of a Ultra-Wideband Monopole Antenna Using Sequential Domain Patching Algorithm with Automated Patch Size Selection |
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199 | (6) |
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9.7.1 Antenna Geometry and Design Objectives |
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199 | (1) |
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9.7.2 Antenna Models and Extreme Pareto Designs |
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200 | (1) |
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200 | (2) |
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9.7.4 Comparison with Benchmark Algorithms |
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202 | (3) |
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9.8 Design of a 14-Variable Multi-Input Multi-Output Antenna Using Design Space Reduction and Co-Kriging |
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205 | (6) |
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9.8.1 Antenna Description and Design Objectives |
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206 | (1) |
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9.8.2 Antenna Models and Design Space Reduction |
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207 | (1) |
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207 | (2) |
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209 | (2) |
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9.9 Optimization of Broadband Quasi-Yagi Antenna Using Multi-Objective Evolutionary Algorithm and Rotational Space Reduction |
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211 | (11) |
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9.9.1 Antenna Description and Design Objectives |
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212 | (1) |
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9.9.2 Design Space Reduction and Kriging Model Construction |
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213 | (1) |
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214 | (3) |
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9.9.4 Experimental Validation |
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217 | (5) |
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222 | (3) |
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10 Selected Topics and Practical Issues |
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225 | (18) |
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10.1 Scalability of Surrogate-Assisted Multi-Objective Optimization Algorithm |
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225 | (9) |
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226 | (2) |
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228 | (4) |
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10.1.3 Analysis of the Algorithm Scalability |
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232 | (2) |
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10.2 Statistical Analysis of Multi-Objective Evolutionary Algorithm-Based Optimization with Kriging Surrogates |
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234 | (3) |
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10.3 Patch Size Setup Trade-Offs for Sequential Domain Patching Algorithm |
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237 | (5) |
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237 | (2) |
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239 | (1) |
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240 | (2) |
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242 | (1) |
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11 Applications in Other Engineering Disciplines |
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243 | (20) |
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11.1 Multi-Objective Design of Impedance Matching Transformers |
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243 | (6) |
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11.1.1 Compact Microwave Circuits: Design Challenges |
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244 | (1) |
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11.1.2 Transformer Structure and Models |
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245 | (1) |
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11.1.3 Results and Comparisons |
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246 | (1) |
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247 | (2) |
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11.2 Multi-Objective Optimization of Compact Couplers |
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249 | (6) |
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11.2.1 Coupler Structure and Problem Formulation |
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250 | (1) |
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11.2.2 Low-Fidelity Model Space Mapping Surrogate |
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251 | (1) |
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11.2.3 Optimization Algorithm |
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252 | (1) |
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11.2.4 Numerical Results and Experimental Validation |
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253 | (2) |
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11.3 Multi-Objective Optimization of Transonic Airfoils |
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255 | (7) |
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11.3.1 Transonic Airfoil Shape Problem Formulation |
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255 | (1) |
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11.3.2 Computational Models |
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256 | (3) |
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11.3.3 Case Study and Results |
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259 | (3) |
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262 | (1) |
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12 Applications of Multi-Objective Optimization |
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263 | (22) |
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12.1 Performance Comparison of Ultra-Wideband Antennas |
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263 | (8) |
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12.1.1 Antenna Comparison Using Pareto Sets |
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264 | (2) |
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12.1.2 Antenna Structures |
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266 | (2) |
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12.1.3 Pareto Fronts Identification Using Sequential Domain Patching |
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268 | (2) |
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12.1.4 Structure Comparison |
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270 | (1) |
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12.2 Performance Comparison of Rectangular Ultra-Wideband Monopoles |
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271 | (2) |
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12.2.1 Antenna Description |
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271 | (1) |
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12.2.2 Multi-Objective-Based Performance Comparison |
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272 | (1) |
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12.3 Optimum Architecture Selection of Compact Impedance Matching Transformers |
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273 | (12) |
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12.3.1 CMRC-Based Miniaturization: Architecture Selection Problem |
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273 | (3) |
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12.3.2 Generation of Pareto Fronts |
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276 | (3) |
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12.3.3 Numerical Results and Comparisons |
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279 | (6) |
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13 Discussion and Recommendations |
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285 | (6) |
References |
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291 | (24) |
Index |
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315 | |