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dc.contributor.editorRoeva, Olympia
dc.date.accessioned2021-04-20T15:24:19Z
dc.date.available2021-04-20T15:24:19Z
dc.date.issued2012
dc.identifierONIX_20210420_9789535101468_1079
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/65722
dc.description.abstractThe book addresses some of the most recent issues, with the theoretical and methodological aspects, of evolutionary multi-objective optimization problems and the various design challenges using different hybrid intelligent approaches. Multi-objective optimization has been available for about two decades, and its application in real-world problems is continuously increasing. Furthermore, many applications function more effectively using a hybrid systems approach. The book presents hybrid techniques based on Artificial Neural Network, Fuzzy Sets, Automata Theory, other metaheuristic or classical algorithms, etc. The book examines various examples of algorithms in different real-world application domains as graph growing problem, speech synthesis, traveling salesman problem, scheduling problems, antenna design, genes design, modeling of chemical and biochemical processes etc.
dc.languageEnglish
dc.subject.classificationbic Book Industry Communication::U Computing & information technology::UY Computer science::UYQ Artificial intelligenceen_US
dc.subject.otherNeural networks & fuzzy systems
dc.titleReal-World Applications of Genetic Algorithms
dc.typebook
oapen.identifier.doi10.5772/2674
oapen.relation.isPublishedBy78a36484-2c0c-47cb-ad67-2b9f5cd4a8f6
oapen.relation.isbn9789535101468
oapen.relation.isbn9789535156895
oapen.imprintIntechOpen
oapen.pages378


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