Evolutionary Computing in Advanced Manufacturing

This cutting-edge book covers emerging, evolutionary and nature inspired optimization techniques in the field of advanced manufacturing. The complexity of real life advanced manufacturing problems often cannot be solved by traditional engineering or computational methods. Hence, in recent years researchers and practitioners have proposed and developed new strands of advanced, intelligent techniques and methodologies. Evolutionary computing approaches are introduced in the context of a wide range of manufacturing activities, and through the examination of practical problems and their solutions, readers will gain confidence to apply these powerful computing solutions. The initial chapters introduce and discuss the well established evolutionary algorithm, to help readers to understand the basic building blocks and steps required to successfully implement their own solutions to real life advanced manufacturing problems. In the later chapters, modified and improved versions of evolutionary algorithms are discussed. The book concludes with appendices which provide general descriptions of several evolutionary algorithms.

Table of Contents

1. Production Planning using Genetic Algorithm
2. Process Planning through Ant Colony Optimization
3. Introducing a Hybrid Genetic Algorithm for Integration of Set Up and Process Planning
4. Design for Supply Chain with Product Development Issues Using Cellular Particle Swarm Optimization (CPSO) Technique
5. Genetic Algorithms with Chromosome Differentiation (GACD) Based Approach for Process Plan Selection Problems
6. Operation Allocation in Flexible Manufacturing System Using Immune Algorithm
7. Tool Selection in FMS an Hybrid SA-TABU Algorithm Based Approach
8. Integrating AGVs and Production Planning with Memetic Particle Swarm Optimization
9. Simulation-based Aircraft Assembly Planning Using a Self-Guided Ant Colony Algorithm
10. Applications of Evolutionary Computing to Additive Manufacturing
11. Multiple Fault Diagnosis Using Psycho-Clonal Algorithms
12. Platform Formation Under Stochastic Demand
13. A Hybrid Particle Swarm and Ant Colony Optimizer for Multi-attribute Partnership Selection in Virtual Enterprises