LEADER 03598nam  22007335  450 
001 996465880403316
005 20230406062128.0
010   $a3-642-19893-7
024 7 $a10.1007/978-3-642-19893-9
035   $a(CKB)2670000000076066
035   $a(SSID)ssj0000536466
035   $a(PQKBManifestationID)11354909
035   $a(PQKBTitleCode)TC0000536466
035   $a(PQKBWorkID)10563658
035   $a(PQKB)11351770
035   $a(DE-He213)978-3-642-19893-9
035   $a(MiAaPQ)EBC3066616
035   $a(PPN)151589739
035   $a(EXLCZ)992670000000076066
100   $a20110325d2011      u|             0
101 0 $aeng
135   $aurnn#008mamaa
181   $ctxt
182   $cc
183   $acr
200 10$aEvolutionary Multi-Criterion Optimization$b[electronic resource] $e6th International Conference, EMO 2011, Ouro Preto, Brazil, April 5-8, 2011, Proceedings /$fedited by Ricardo H.C. Takahashi, Kalyanmoy Deb, Elizabeth F. Wanner, Salvatore Greco
205   $a1st ed. 2011.
210  1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2011.
215   $a1 online resource (XV, 620 p.)
225 1 $aTheoretical Computer Science and General Issues,$x2512-2029 ;$v6576
300   $aBibliographic Level Mode of Issuance: Monograph
311   $a3-642-19892-9 
320   $aIncludes bibliographical references and index.
330   $aThis book constitutes the refereed proceedings of the 6th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2011, held in Ouro Preto, Brazil, in April 2011. The 42 revised full papers presented were carefully reviewed and selected from 83 submissions. The papers deal with fundamental questions of EMO theory, such as the development of algorithmically efficient tools for the evaluation of solution-set quality , the theoretical questions related to solution archiving and others. They report on the continuing effort in the development of algorithms, either for dealing with particular classes of problems or for new forms of processing the problem information. Almost one third of the papers is related to EMO applications in a diversity of fields. Eleven papers are devoted to promote the interaction with the related field of Multi-Criterion Decision Making (MCDM).
410  0$aTheoretical Computer Science and General Issues,$x2512-2029 ;$v6576
606   $aAlgorithms
606   $aNumerical analysis
606   $aArtificial intelligence
606   $aMathematical optimization
606   $aComputational intelligence
606   $aAlgorithms
606   $aNumerical Analysis
606   $aArtificial Intelligence
606   $aOptimization
606   $aComputational Intelligence
615  0$aAlgorithms.
615  0$aNumerical analysis.
615  0$aArtificial intelligence.
615  0$aMathematical optimization.
615  0$aComputational intelligence.
615 14$aAlgorithms.
615 24$aNumerical Analysis.
615 24$aArtificial Intelligence.
615 24$aOptimization.
615 24$aComputational Intelligence.
676   $a005.1
702   $aTakahashi$b Ricardo H.C$4edt$4http://id.loc.gov/vocabulary/relators/edt
702   $aDeb$b Kalyanmoy$4edt$4http://id.loc.gov/vocabulary/relators/edt
702   $aWanner$b Elizabeth F$4edt$4http://id.loc.gov/vocabulary/relators/edt
702   $aGreco$b Salvatore$4edt$4http://id.loc.gov/vocabulary/relators/edt
906   $aBOOK
912   $a996465880403316
996   $aEvolutionary Multi-Criterion Optimization$9771896
997   $aUNISA