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Acknowledgements; Contents; Part IIntroduction and Overview; 1 Brief History and Overview of Intelligent Optimization Algorithms; 1.1 ... Introduction; 1.2 ... Brief History of Intelligent Optimization Algorithms; 1.3 ... Classification of Intelligent Algorithms; 1.4 ... Brief Review of Typical Intelligent Optimization Algorithms; 1.4.1 Review of Evolutionary Learning Algorithms; 1.4.1.1 Genetic Algorithm; 1.4.1.2 Immune Algorithm; 1.4.2 Review of Neighborhood Search Algorithms; 1.4.2.1 Simulated Annealing Algorithm; 1.4.2.2 Iterative Local Search; 1.4.3 Review of Swarm Intelligence Algorithm.
1.4.3.1 Ant Colony Optimization1.4.3.2 Particle Swarm Optimization; 1.5 ... The Classification of Current Studies on Intelligent Optimization Algorithm; 1.5.1 Algorithm Innovation; 1.5.2 Algorithm Improvement; 1.5.3 Algorithm Hybridization; 1.5.4 Algorithm Parallelization; 1.5.5 Algorithm Application; 1.6 ... Development Trends; 1.6.1 Intellectualization; 1.6.2 Service-Orientation; 1.6.3 Application-Oriented; 1.6.4 User-Centric; 1.7 ... Summary; References; 2 Recent Advances of Intelligent Optimization Algorithm in Manufacturing; 2.1 ... Introduction.
2.2 ... Classification of Optimization Problems in Manufacturing2.2.1 Numerical Function Optimization; 2.2.2 Parameter Optimization; 2.2.3 Detection and Classification; 2.2.4 Combinatorial Scheduling; 2.2.5 Multi-disciplinary Optimization; 2.2.6 Summary of the Five Types of Optimization Problems in Manufacturing; 2.3 ... Challenges for Addressing Optimization Problems in Manufacturing; 2.3.1 Balance of Multi-objectives; 2.3.2 Handling of Multi-constraints; 2.3.3 Extraction of Priori Knowledge; 2.3.4 Modeling of Uncertainty and Dynamics; 2.3.5 Transformation of Qualitative and Quantitative Features.
2.3.6 Simplification of Large-Scale Solution Space2.3.7 Jumping Out of Local Convergence; 2.4 ... An Overview of Optimization Methods in Manufacturing; 2.4.1 Empirical-Based Method; 2.4.2 Prediction-Based Method; 2.4.3 Simulation-Based Method; 2.4.4 Model-Based Method; 2.4.5 Tool-Based Method; 2.4.6 Advanced-Computing-Technology-Based Method; 2.4.7 Summary of Studies on Solving Methods; 2.5 ... Intelligent Optimization Algorithms for Optimization Problems in Manufacturing; 2.6 ... Challenges of Applying Intelligent Optimization Algorithms in Manufacturing; 2.6.1 Problem Modeling.
2.6.2 Algorithm Selection2.6.3 Encoding Scheming; 2.6.4 Operator Designing; 2.7 ... Future Approaches for Manufacturing Optimization; 2.8 ... Future Requirements and Trends of Intelligent Optimization Algorithm in Manufacturing; 2.8.1 Integration; 2.8.2 Configuration; 2.8.3 Parallelization; 2.8.4 Executing as Service; 2.9 ... Summary; References; Part IIDesign and Implementation; 3 Dynamic Configuration of Intelligent Optimization Algorithms; 3.1 ... Concept and Mainframe of DC-IOA; 3.1.1 Mainframe of DC-IOA; 3.1.2 Problem Specification and Construction of Algorithm Library in DC-IOA; 3.2 ... Case Study.
1.4.3.1 Ant Colony Optimization1.4.3.2 Particle Swarm Optimization; 1.5 ... The Classification of Current Studies on Intelligent Optimization Algorithm; 1.5.1 Algorithm Innovation; 1.5.2 Algorithm Improvement; 1.5.3 Algorithm Hybridization; 1.5.4 Algorithm Parallelization; 1.5.5 Algorithm Application; 1.6 ... Development Trends; 1.6.1 Intellectualization; 1.6.2 Service-Orientation; 1.6.3 Application-Oriented; 1.6.4 User-Centric; 1.7 ... Summary; References; 2 Recent Advances of Intelligent Optimization Algorithm in Manufacturing; 2.1 ... Introduction.
2.2 ... Classification of Optimization Problems in Manufacturing2.2.1 Numerical Function Optimization; 2.2.2 Parameter Optimization; 2.2.3 Detection and Classification; 2.2.4 Combinatorial Scheduling; 2.2.5 Multi-disciplinary Optimization; 2.2.6 Summary of the Five Types of Optimization Problems in Manufacturing; 2.3 ... Challenges for Addressing Optimization Problems in Manufacturing; 2.3.1 Balance of Multi-objectives; 2.3.2 Handling of Multi-constraints; 2.3.3 Extraction of Priori Knowledge; 2.3.4 Modeling of Uncertainty and Dynamics; 2.3.5 Transformation of Qualitative and Quantitative Features.
2.3.6 Simplification of Large-Scale Solution Space2.3.7 Jumping Out of Local Convergence; 2.4 ... An Overview of Optimization Methods in Manufacturing; 2.4.1 Empirical-Based Method; 2.4.2 Prediction-Based Method; 2.4.3 Simulation-Based Method; 2.4.4 Model-Based Method; 2.4.5 Tool-Based Method; 2.4.6 Advanced-Computing-Technology-Based Method; 2.4.7 Summary of Studies on Solving Methods; 2.5 ... Intelligent Optimization Algorithms for Optimization Problems in Manufacturing; 2.6 ... Challenges of Applying Intelligent Optimization Algorithms in Manufacturing; 2.6.1 Problem Modeling.
2.6.2 Algorithm Selection2.6.3 Encoding Scheming; 2.6.4 Operator Designing; 2.7 ... Future Approaches for Manufacturing Optimization; 2.8 ... Future Requirements and Trends of Intelligent Optimization Algorithm in Manufacturing; 2.8.1 Integration; 2.8.2 Configuration; 2.8.3 Parallelization; 2.8.4 Executing as Service; 2.9 ... Summary; References; Part IIDesign and Implementation; 3 Dynamic Configuration of Intelligent Optimization Algorithms; 3.1 ... Concept and Mainframe of DC-IOA; 3.1.1 Mainframe of DC-IOA; 3.1.2 Problem Specification and Construction of Algorithm Library in DC-IOA; 3.2 ... Case Study.