000 03750nam a22004935i 4500
001 978-3-540-32839-1
003 DE-He213
005 20170628034455.0
007 cr nn 008mamaa
008 100301s2006 gw | s |||| 0|eng d
020 _a9783540328391
_9978-3-540-32839-1
024 7 _a10.1007/3-540-32839-4
_2doi
050 4 _aTA329-348
050 4 _aTA640-643
072 7 _aTBJ
_2bicssc
072 7 _aMAT003000
_2bisacsh
082 0 4 _a519
_223
100 1 _aNedjah, Nadia.
_eeditor.
245 1 0 _aParallel Evolutionary Computations
_h[electronic resource] /
_cedited by Nadia Nedjah, Luiza de Macedo Mourelle, Enrique Alba.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg,
_c2006.
300 _aXXIII, 201 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aStudies in Computational Intelligence,
_x1860-949X ;
_v22
505 0 _aParallel Evolutionary Optimization -- A Model for Parallel Operators in Genetic Algorithms -- Parallel Evolutionary Multiobjective Optimization -- Parallel Hardware for Genetic Algorithms -- A Reconfigurable Parallel Hardware for Genetic Algorithms -- Reconfigurable Computing and Parallelism for Implementing and Accelerating Evolutionary Algorithms -- Distributed Evolutionary Computation -- Performance of Distributed GAs on DNA Fragment Assembly -- On Parallel Evolutionary Algorithms on the Computational Grid -- Parallel Evolutionary Algorithms on Consumer-Level Graphics Processing Unit -- Parallel Particle Swarm Optimization -- Intelligent Parallel Particle Swarm Optimization Algorithms -- Parallel Ant Colony Optimization for 3D Protein Structure Prediction using the HP Lattice Model.
520 _a"Parallel Evolutionary Computation" focuses on the aspects related to the parallelization of evolutionary computations, such as parallel genetic operators, parallel fitness evaluation, distributed genetic algorithms, and parallel hardware implementations, as well as on their impact on several applications. The book is divided into four parts. The first part deals with a clear software-like and algorithmic vision on parallel evolutionary optimizations. The second part is about hardware implementations of genetic algorithms, a valuable topic which is hard to find in the present literature. The third part treats the problem of distributed evolutionary computation and presents three interesting applications wherein parallel EC new ideas are featured. Finally, the last part deals with the up-to-date field of parallel particle swarm optimization to illustrate the intrinsic similarities and potential extensions to techniques in this domain. The book offers a wide spectrum of sample works developed in leading research throughout the world about parallel implementations of efficient techniques at the heart of computational intelligence. It will be useful both for beginners and experienced researchers in the field of computational intelligence.
650 0 _aEngineering.
650 0 _aArtificial intelligence.
650 0 _aEngineering mathematics.
650 1 4 _aEngineering.
650 2 4 _aAppl.Mathematics/Computational Methods of Engineering.
650 2 4 _aArtificial Intelligence (incl. Robotics).
700 1 _aMourelle, Luiza de Macedo.
_eeditor.
700 1 _aAlba, Enrique.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783540328377
830 0 _aStudies in Computational Intelligence,
_x1860-949X ;
_v22
856 4 0 _uhttp://dx.doi.org/10.1007/3-540-32839-4
912 _aZDB-2-ENG
999 _c20030
_d20030