Particle Swarm Optimization
1st Edition
Published on 7. February 2006
Book
Hardback
244 pages
978-1-905209-04-0 (ISBN)
Description
This is the first book devoted entirely to Particle Swarm Optimization (PSO), which is a non-specific algorithm, similar to evolutionary algorithms, such as taboo search and ant colonies. Since its original development in 1995, PSO has mainly been applied to continuous-discrete heterogeneous strongly non-linear numerical optimization and it is thus used almost everywhere in the world. Its convergence rate also makes it a preferred tool in dynamic optimization.
More details
Language
English
Place of publication
London
United Kingdom
Target group
Professional and scholarly
Product notice
Unsewn / adhesive bound
Paper over boards
Dimensions
Height: 240 mm
Width: 161 mm
Thickness: 18 mm
Weight
536 gr
ISBN-13
978-1-905209-04-0 (9781905209040)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Person
Maurice Clerc is recognized as one of the foremost PSO specialists in the world. A former France Telecom Research and Development engineer, he maintains his research activities as a consultant for the XPS (eXtended Particle Swarm) project.
Content
Foreword. Introduction.
Part 1: Particle Swarm Optimization.
Chapter 1. What is a difficult problem?
Chapter 2. On a table corner.
Chapter 3. First formulations.
Chapter 4. Benchmark set.
Chapter 5. Mistrusting chance.
Chapter 6. First results.
Chapter 7. Swarm: memory and influence graphs.
Chapter 8. Distributions of proximity.
Chapter 9. Optimal parameter settings.
Chapter 10. Adaptations.
Chapter 11. TRIBES or co-operation of tribes.
Chapter 12. On the constraints.
Chapter 13. Problems and applications.
Chapter 14. Conclusion.
Part 2: Outlines.
Chapter 15. On parallelism.
Chapter 16. Combinatorial problems.
Chapter 17. Dynamics of a swarm.
Chapter 18. Techniques and alternatives.
Further Information.
Bibliography.
Index.
Part 1: Particle Swarm Optimization.
Chapter 1. What is a difficult problem?
Chapter 2. On a table corner.
Chapter 3. First formulations.
Chapter 4. Benchmark set.
Chapter 5. Mistrusting chance.
Chapter 6. First results.
Chapter 7. Swarm: memory and influence graphs.
Chapter 8. Distributions of proximity.
Chapter 9. Optimal parameter settings.
Chapter 10. Adaptations.
Chapter 11. TRIBES or co-operation of tribes.
Chapter 12. On the constraints.
Chapter 13. Problems and applications.
Chapter 14. Conclusion.
Part 2: Outlines.
Chapter 15. On parallelism.
Chapter 16. Combinatorial problems.
Chapter 17. Dynamics of a swarm.
Chapter 18. Techniques and alternatives.
Further Information.
Bibliography.
Index.