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.ACO algorithm can be used to solve both static and dynamic combinatorial optimization problems. Static problems are those problems in which the characteristics of the problems remain unchanged throughout its solution procedure. Dynamicanbsp;...
|Title||:||Multi-objective Swarm Intelligence|
|Author||:||Satchidananda Dehuri, Alok Kumar Jagadev, Mrutyunjaya Panda|
|Publisher||:||Springer - 2015-03-10|