Configurable Intelligent Optimization Algorithm: Design and Practice in Manufacturing (Springer Series in Advanced Manufacturing)

Presenting the concept and design and implementation of configurable intelligent optimization algorithms in manufacturing systems, this book provides a new configuration method to optimize manufacturing processes. It provides a comprehensive elaboration of basic intelligent optimization algorithms, and demonstrates how their improvement, hybridization and parallelization can be applied to manufacturing. Furthermore, various applications of these intelligent optimization algorithms are exemplified in detail, chapter by chapter. The intelligent optimization algorithm is not just a single algorithm; instead it is a general advanced optimization mechanism which is highly scalable with robustness and randomness. Therefore, this book demonstrates the flexibility of these algorithms, as well as their robustness and reusability in order to solve mass complicated problems in manufacturing. Since the genetic algorithm was presented decades ago, a large number of intelligent optimization algorithms and their improvements have been developed. However, little work has been done to extend their applications and verify their competence in solving complicated problems in manufacturing. This book will provide an invaluable resource to students, researchers, consultants and industry professionals interested in engineering optimization. It will also be particularly useful to three groups of readers: algorithm beginners, optimization engineers and senior algorithm designers. It offers a detailed description of intelligent optimization algorithms to algorithm beginners; recommends new configurable design methods for optimization engineers, and provides future trends and challenges of the new configuration mechanism to senior algorithm designers. Front Matter....Pages i-xiii Front Matter....Pages 1-2 Brief History and Overview of Intelligent Optimization Algorithms....Pages 3-33 Recent Advances of Intelligent Optimization Algorithm in Manufacturing....Pages 35-80 Front Matter....Pages 81-82 Dynamic Configuration of Intelligent Optimization Algorithms....Pages 83-105 Improvement and Hybridization of Intelligent Optimization Algorithm....Pages 107-126 Parallelization of Intelligent Optimization Algorithm....Pages 127-154 Front Matter....Pages 155-155 GA-BHTR for Partner Selection Problem....Pages 157-189 CLPS-GA for Energy-Aware Cloud Service Scheduling....Pages 191-224 Front Matter....Pages 225-225 SFB-ACO for Submicron VLSI Routing Optimization with Timing Constraints....Pages 227-256 A Hybrid RCO for Dual Scheduling of Cloud Service and Computing Resource in Private Cloud....Pages 257-287 Front Matter....Pages 289-289 Computing Resource Allocation with PEADGA....Pages 291-331 Job Shop Scheduling with FPGA-Based F4SA....Pages 333-347 Front Matter....Pages 349-349 Future Trends and Challenges....Pages 351-361