Multi-objective Swarm Intelligence

The aim of this book is to understand the state-of-the-art theoretical and practical advances of swarm intelligence. It comprises seven contemporary relevant chapters. In chapter 1, a review of Bacteria Foraging Optimization (BFO) techniques for both single and multiple criterions problem is presented. A survey on swarm intelligence for multiple and many objectives optimization is presented in chapter 2 along with a topical study on EEG signal analysis. Without compromising the extensive simulation study, a comparative study of variants of MOPSO is provided in chapter 3. Intractable problems like subset and job scheduling problems are discussed in chapters 4 and 7 by different hybrid swarm intelligence techniques. An attempt to study image enhancement by ant colony optimization is made in chapter 5. Finally, chapter 7 covers the aspect of uncertainty in data by hybrid PSO.

Recent research on Multi objective Swarm Intelligence Presents theoretical advances and applications Written by leading experts in the field Includes supplementary material: sn.pub/extras

Inhalt
Introduction.- Behavior of Bacterial Colony.- E.coli Bacterial Colonies.- Optimization based on E.coli Bacterial Colony.- Classification of BFO Algorithm.- Multi-objective optimization based on BF.- An overview of BFO Applications.- Conclusion.