Multi-objective Swarm Intelligence : theoretical advances and applications
Title By: Dehuri, Satchidananda [Edited by] | Jagadev, Alok Kumar [Edited by] | Panda, Mrutyunjaya [Edited by]
Material type:![](/opac-tmpl/lib/famfamfam/BK.png)
Item type | Home library | Call number | Status | Notes | Date due | Barcode | Item holds |
---|---|---|---|---|---|---|---|
REGULAR | University of Wollongong in Dubai Main Collection | 006.3 MU LT (Browse shelf) | Available | May2018 | T0059793 |
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.
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.