Multi-objective swarm intelligence: theoretical advances and applications - volume 592

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.