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Multi-objective Swarm Intelligence

Theoretical Advances and Applications

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.

The purpose of this volume entitled “Multi-objective Swarm Intelligence:
Theoretical Advances and Applications” is to attract a wide range of researchers
and readers from all fields of science and engineering performing
interdisciplinary research based on swarm intelligence methodologies to
optimize intractable problems, which are either in the form of single or multi-
objective optimization. Multi-objective optimization deals with the simultaneous
optimization of two or more objectives ...