Multi-objective Swarm Intelligence electronic resource Theoretical Advances and Applications / edited by Satchidananda Dehuri, Alok Kumar Jagadev, Mrutyunjaya Panda.
Material type: TextSeries: Studies in Computational IntelligencePublication details: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2015Description: XIV, 201 p. 60 illus., 11 illus. in color. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9783662463093Subject(s): engineering | Artificial intelligence | Computational Intelligence | Engineering | Computational Intelligence | Artificial Intelligence (incl. Robotics)DDC classification: 006.3 LOC classification: Q342Online resources: Click here to access onlineIntroduction -- 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. .
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