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020 _a9783540709282
_9978-3-540-70928-2
024 7 _a10.1007/978-3-540-70928-2
_2doi
050 4 _aQA76.9.A43
072 7 _aUMB
_2bicssc
072 7 _aCOM051300
_2bisacsh
072 7 _aUMB
_2thema
082 0 4 _a518.1
_223
245 1 0 _aEvolutionary Multi-Criterion Optimization
_h[electronic resource] :
_b4th International Conference, EMO 2007, Matsushima, Japan, March 5-8, 2007, Proceedings /
_cedited by Shigeru Obayashi, Kalyanmoy Deb, Carlo Poloni, Tomoyuki Hiroyasu, Tadahiko Murata.
250 _a1st ed. 2007.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2007.
300 _aXIX, 954 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aTheoretical Computer Science and General Issues,
_x2512-2029 ;
_v4403
505 0 _aInvited Talks -- Algorithm Design -- Algorithm Improvements -- Alternative Methods -- Applications -- Engineering Design -- Many Objectives -- Objective Handling -- Performance Assessments.
520 _aMulticriterion optimization refers to problems with two or more objectives (normally in conflict with each other) which must be simultaneously satisfied. Evolutionary algorithms have been used for solving multicriterion optimization problems for over two decades, gaining an increasing attention from industry. The 4th International Conference on Evolutionary Multi-criterion Optimization (EMO2007) was held during March 5-8, 2007, in Matsushima/Sendai, Japan. This was the fourth international conference dedicated entirely to this important topic, following the successful EMO 2001, EMO 2003 and EMO 2005 conferences, which were held in Zürich, Switzerland in March 2001, in Faro, Portugal in April 2003, and in Guanajuato, México in March 2005. EMO2007 was hosted by the Institute of Fluid Science, Tohoku University. EMO2007 was co-hosted by the Graduate School of Information Sciences, Tohoku University, the Japan Aerospace Exploration Agency (JAXA), and the Policy Grid Computing Laboratory, Kansai University. The EMO2007 scientific program included four keynote speakers: Hirotaka Nakayama on aspiration level methods, Kay Chen Tan on large and computationally intensive real-world MO optimization problems, Carlos Fonseca on decision making, and Gary B. Lamont on design of large-scale network centric systems.
650 0 _aAlgorithms.
_93390
650 0 _aNumerical analysis.
_94603
650 0 _aArtificial intelligence.
_93407
650 1 4 _aAlgorithms.
_93390
650 2 4 _aNumerical Analysis.
_94603
650 2 4 _aArtificial Intelligence.
_93407
700 1 _aObayashi, Shigeru.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9173258
700 1 _aDeb, Kalyanmoy.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9173259
700 1 _aPoloni, Carlo.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9173260
700 1 _aHiroyasu, Tomoyuki.
_eeditor.
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_4http://id.loc.gov/vocabulary/relators/edt
_9173261
700 1 _aMurata, Tadahiko.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9173262
710 2 _aSpringerLink (Online service)
_9173263
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783540709275
776 0 8 _iPrinted edition:
_z9783540835486
830 0 _aTheoretical Computer Science and General Issues,
_x2512-2029 ;
_v4403
_9173264
856 4 0 _uhttps://doi.org/10.1007/978-3-540-70928-2
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