Multi-objective Swarm Intelligence  Theoretical Advances and Applications /  [electronic resource] : 
edited by Satchidananda Dehuri, Alok Kumar Jagadev, Mrutyunjaya Panda. 
 - XIV, 201 p. 60 illus., 11 illus. in color.  online resource. 
 - Studies in Computational Intelligence,  592  1860-949X ; .
 - Studies in Computational Intelligence,  592 .
<br/><br/>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. 
<br/><br/> 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.       . 
<br/><br/><label>ISBN: </label>9783662463093 
<br/><br/><label>Standard No.: </label>10.1007/978-3-662-46309-3  doi 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Engineering.<br/>Artificial intelligence.<br/>Computational intelligence.<br/>Engineering.<br/>Computational Intelligence.<br/>Artificial Intelligence (incl. Robotics).
<br/><br/><label>LC Class. No.: </label>Q342 
<br/><br/><label>Dewey Class. No.: </label>006.3