| Introduction | p. 1 |
| Manufacturing Systems | p. 1 |
| The Manufacturing Process | p. 3 |
| Computing Technologies | p. 4 |
| About This Book | p. 9 |
| References | p. 11 |
| Metaheuristic Optimization in Certain and Uncertain Environments | p. 13 |
| Introduction | p. 13 |
| Metaheuristic Approaches to Optimization | p. 13 |
| Genetic Algorithms | p. 14 |
| Simulated Annealing | p. 22 |
| Tabu Search | p. 26 |
| Differential Evolution (DE) | p. 27 |
| Particle Swarm Optimization (PSO) | p. 32 |
| Other Methods | p. 34 |
| Hybrid Approaches to Optimization | p. 36 |
| Applications for Manufacturing Planning and Operation | p. 38 |
| Logistic Optimization Using Hybrid Tabu Search | p. 39 |
| Sequencing Planning for a Mixed-model Assembly Line Using SA | p. 48 |
| General Scheduling Considering Human-Machine Cooperation | p. 53 |
| Optimization under Uncertainty | p. 60 |
| A GA to Derive an Insensitive Solution against Uncertain Parameters | p. 60 |
| Flexible Logistic Network Design Optimization | p. 65 |
| Chapter Summary | p. 71 |
| References | p. 72 |
| Multi-objective Optimization Through Soft Computing Approaches | p. 77 |
| Introduction | p. 77 |
| Multi-objective Metaheuristic Methods | p. 79 |
| Aggregating Function Approaches | p. 80 |
| Population-oriented Approaches | p. 80 |
| Pareto-based Approaches | p. 82 |
| Multi-objective Optimization in Terms of Soft Computing | p. 87 |
| Value Function Modeling Using Artificial Neural Networks | p. 88 |
| Hybrid GA for Solving MIP under Multi-objectives | p. 91 |
| MOON2R and MOON2 | p. 95 |
| Applications of MOSC for Manufacturing Optimization | p. 105 |
| Multi-objective Site Location of Waste Disposal Facilities | p. 106 |
| Multi-objective Scheduling of Flow Shop | p. 108 |
| Artificial Product Design | p. 112 |
| Chapter Summary | p. 121 |
| References | p. 122 |
| Cellular Neural Networks in Intelligent Sensing and Diagnosis | p. 125 |
| The Cellular Neural Networkas an Associative Memory | p. 125 |
| Design Method of CNN | p. 128 |
| A Method Using Singular Value Decomposition | p. 128 |
| Multi-output Function Design | p. 131 |
| Un-uniform Neighborhood | p. 135 |
| Multi-memory Tables for CNN | p. 140 |
| Applications in Intelligent Sensing and Diagnosis | p. 143 |
| Liver Disease Diagnosis | p. 143 |
| Abnormal Car Sound Detection | p. 147 |
| Pattern Classification | p. 152 |
| Chapter Summary | p. 155 |
| References | p. 156 |
| The Wavelet Transform in Signal and Image Processing | p. 159 |
| Introduction to Wavelet Transforms | p. 159 |
| The Continuous Wavelet Transform | p. 160 |
| The Conventional Continuous Wavelet Transform | p. 160 |
| The New Wavelet: The RI-Spline Wavelet | p. 162 |
| Fast Algorithms in the Frequency Domain | p. 167 |
| Creating a Novel Real Signal Mother Wavelet | p. 173 |
| Translation Invariance Complex Discrete Wavelet Transforms | p. l78 |
| Traditional Discrete Wavelet Transforms | p. 180 |
| RI-spline Wavelet for Complex Discrete Wavelet Transforms | p. 182 |
| Coherent Dual-tree Algorithm | p. 185 |
| 2-D Complex Discrete Wavelet Transforms | p. 189 |
| Applications in Signal and Image Processing | p. 194 |
| Fractal Analysis Using the Fast Continuous Wavelet Transform | p. 194 |
| Knocking Detection Using Wavelet Instantaneous Correlation | p. 200 |
| De-noising by Complex Discrete Wavelet Transforms | p. 205 |
| Image Processing and Direction Selection | p. 212 |
| Chapter Summary | p. 217 |
| References | p. 219 |
| Integration of Information Systems | p. 221 |
| Introduction | p. 221 |
| Enterprise Systems | p. 224 |
| MES Systems | p. 224 |
| Integration Layers | p. 225 |
| Integration Technologies | p. 225 |
| Database Integration | p. 225 |
| Remote Procedure Calls | p. 226 |
| OPC | p. 227 |
| Publishand Subscribe | p. 227 |
| Web Services | p. 228 |
| Multi-agent Systems | p. 229 |
| FIPA: A Standard for Agent Systems | p. 230 |
| Applications of Multi-agent Systems in Manufacturing | p. 232 |
| Multi-agent System Example | p. 232 |
| Standard Reference Models | p. 236 |
| ISO TC184 | p. 236 |
| IEC/ISO 62264 | p. 237 |
| Formal Languages | p. 240 |
| EXPRESS | p. 240 |
| Ontology Languages | p. 240 |
| OWL | p. 241 |
| Matchmaking Agents Revisited | p. 242 |
| Upper Ontologies | p. 243 |
| ISO 15926 | p. 244 |
| Connectivity and Composition | p. 244 |
| Physical Quantities | p. 246 |
| Time-reasoning | p. 249 |
| Chapter Summary | p. 250 |
| References | p. 251 |
| Summary | p. 253 |
| Introduction to IDEF0 | p. 259 |
| References | p. 261 |
| The Basis of Optimization Under a Single Objective | p. 263 |
| Introduction | p. 263 |
| Linear Programming and Some Remarks on Its Advances | p. 264 |
| Non-linear Programs | p. 269 |
| References | p. 275 |
| The Basis of Optimization Under Multiple Objectives | p. 277 |
| Binary Relations and Preference Order | p. 277 |
| Traditional Methods | p. 279 |
| Multi-objective Analysis | p. 279 |
| Prior Articulation Methods of MOP | p. 281 |
| Some Interactive Methods of MOP | p. 283 |
| Worth Assessment and the Analytic Hierarchical Process | p. 290 |
| Worth Assessment | p. 290 |
| The Analytic Hierarchy Process (AHP) | p. 291 |
| References | p. 294 |
| The Basis of Neural Networks | p. 297 |
| The Back Propagation Network | p. 297 |
| The Radial-basis Function Network | p. 299 |
| References | p. 301 |
| The Level Partition Algorithm of ISM | p. 303 |
| References | p. 305 |
| Index | p. 307 |
| Table of Contents provided by Publisher. All Rights Reserved. |
