000			02044cam a22002415a 4500
999			_c34127 _d34127
001			OCM1ssj0001465620
020			_a9783662463086
020			_a9783662463086
082	0	4	_a006.3 MU LT
245	1	0	_aMulti-objective Swarm Intelligence : _btheoretical advances and applications _cEdited by Satchidananda Dehuri, Alok Kumar Jagadev, Mrutyunjaya Panda.
260			_aLondon : _bSpringer, _cc2015.
300			_axiv, 201 p. ; _bill. ; _c24 cm.
490	1		_aStudies in Computational Intelligence, _x1860-949X ; _v592
505	0		_aIntroduction -- 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.
520			_aThe 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.
650		0	_aEngineering _9780
650		0	_aArtificial intelligence _9370
700	1		_aDehuri, Satchidananda, _eEdited by _939014
700	1		_aJagadev, Alok Kumar, _eEdited by _939015
700	1		_aPanda, Mrutyunjaya, _eEdited by _939016
856			_uhttps://uowd.box.com/s/5tfcyofz1iagzl63whqgic1sfxmdzuij _zLocation Map
942			_2ddc _cREGULAR