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Genetic Algorithms and Genetic Programming

Proposal review

Modern Concepts and Practical Applications

dc.contributor.authorAffenzeller, Michael
dc.contributor.authorWagner, Stefan
dc.contributor.authorWinkler, Stephan
dc.contributor.authorBeham, Andreas
dc.date.accessioned2025-05-12T09:31:48Z
dc.date.available2025-05-12T09:31:48Z
dc.date.issued2009
dc.identifierONIX_20250512_9781420011326_6
dc.identifier.urihttps://library.oapen.org/handle/20.500.12657/101465
dc.description.abstractGenetic Algorithms and Genetic Programming: Modern Concepts and Practical Applications discusses algorithmic developments in the context of genetic algorithms (GAs) and genetic programming (GP). It applies the algorithms to significant combinatorial optimization problems and describes structure identification using HeuristicLab as a platform for al
dc.languageEnglish
dc.relation.ispartofseriesNumerical Insights
dc.subject.classificationthema EDItEUR::U Computing and Information Technology::UY Computer science
dc.subject.classificationthema EDItEUR::U Computing and Information Technology::UM Computer programming / software engineering::UMB Algorithms and data structures
dc.subject.classificationthema EDItEUR::U Computing and Information Technology::UB Information technology: general topics
dc.subject.classificationthema EDItEUR::U Computing and Information Technology::UN Databases::UNF Data mining
dc.subject.otherMichael Affenzeller
dc.subject.othergenetic algorithms
dc.subject.othergenetic programming
dc.subject.otherGA Theory
dc.subject.otherGP Schema theories
dc.subject.othertime series analysis
dc.subject.otherpopulation diversity
dc.subject.otherHeuristic lab
dc.subject.otherCrossover Operators
dc.subject.otherStandard GA
dc.subject.otherCapacitated Vehicle Routing Problem
dc.subject.otherBuilding Block Hypothesis
dc.subject.otherGlobal Optimal Solution
dc.subject.otherSchema Theorem
dc.subject.otherCombinatorial Optimization Problems
dc.subject.otherGP Population
dc.subject.otherGP Test
dc.subject.otherData Set
dc.subject.otherIsland Model
dc.subject.otherGA Application
dc.subject.otherParallel GAs
dc.subject.otherRoc Curve
dc.subject.otherSolution Candidates
dc.subject.otherVRP
dc.subject.otherSequential GA
dc.subject.otherMelanoma Data Set
dc.subject.otherParent Tours
dc.subject.otherM2 M1
dc.subject.otherLinear Rank Selection
dc.titleGenetic Algorithms and Genetic Programming
dc.title.alternativeModern Concepts and Practical Applications
dc.typebook
oapen.identifier.doi10.1201/9781420011326
oapen.relation.isPublishedBy7b3c7b10-5b1e-40b3-860e-c6dd5197f0bb
oapen.relation.isFundedByb5330eea-5b68-4d3e-8fe5-c6b3c1865c2a
oapen.relation.isbn9781420011326
oapen.relation.isbn9781584886297
oapen.relation.isbn9781138114272
oapen.relation.isbn9780429141973
oapen.relation.isbn9781040044254
oapen.imprintChapman and Hall/CRC
oapen.pages379
oapen.grant.number[...]
oapen.identifier.ocn449735109
peerreview.anonymitySingle-anonymised
peerreview.idbc80075c-96cc-4740-a9f3-a234bc2598f1
peerreview.open.reviewNo
peerreview.publish.responsibilityPublisher
peerreview.review.stagePre-publication
peerreview.review.typeProposal
peerreview.reviewer.typeInternal editor
peerreview.reviewer.typeExternal peer reviewer
peerreview.titleProposal review
oapen.review.commentsTaylor & Francis open access titles are reviewed as a minimum at proposal stage by at least two external peer reviewers and an internal editor (additional reviews may be sought and additional content reviewed as required).


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