000 03627nam a22005655i 4500
001 978-3-319-26467-7
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020 _a9783319264677
_9978-3-319-26467-7
024 7 _a10.1007/978-3-319-26467-7
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aTEC009000
_2bisacsh
072 7 _aUYQ
_2thema
082 0 4 _a006.3
_223
100 1 _aAguiar e Oliveira Junior, Hime.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_955597
245 1 0 _aEvolutionary Global Optimization, Manifolds and Applications
_h[electronic resource] /
_cby Hime Aguiar e Oliveira Junior.
250 _a1st ed. 2016.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2016.
300 _aXIII, 137 p. 43 illus., 26 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aStudies in Systems, Decision and Control,
_x2198-4190 ;
_v43
505 0 _aPart I Introductory Information -- Part II Global optimization on manifolds -- Part III Further Applications of fuzzy ASA.
520 _aThis book presents powerful techniques for solving global optimization problems on manifolds by means of evolutionary algorithms, and shows in practice how these techniques can be applied to solve real-world problems. It describes recent findings and well-known key facts in general and differential topology, revisiting them all in the context of application to current optimization problems. Special emphasis is put on game theory problems. Here, these problems are reformulated as constrained global optimization tasks and solved with the help of Fuzzy ASA. In addition, more abstract examples, including minimizations of well-known functions, are also included. Although the Fuzzy ASA approach has been chosen as the main optimizing paradigm, the book suggests that other metaheuristic methods could be used as well. Some of them are introduced, together with their advantages and disadvantages. Readers should possess some knowledge of linear algebra, and of basic concepts of numerical analysis and probability theory. Many necessary definitions and fundamental results are provided, with the formal mathematical requirements limited to a minimum, while the focus is kept firmly on continuous problems. The book offers a valuable resource for students, researchers and practitioners. It is suitable for university courses on optimization and for self-study. .
650 0 _aComputational intelligence.
_97716
650 0 _aEconometrics.
_920971
650 0 _aMathematical optimization.
_94112
650 0 _aStatisticsĀ .
_931616
650 1 4 _aComputational Intelligence.
_97716
650 2 4 _aQuantitative Economics.
_931722
650 2 4 _aContinuous Optimization.
_933915
650 2 4 _aStatistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
_931790
710 2 _aSpringerLink (Online service)
_955598
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783319264660
776 0 8 _iPrinted edition:
_z9783319264684
776 0 8 _iPrinted edition:
_z9783319799582
830 0 _aStudies in Systems, Decision and Control,
_x2198-4190 ;
_v43
_955599
856 4 0 _uhttps://doi.org/10.1007/978-3-319-26467-7
912 _aZDB-2-ENG
912 _aZDB-2-SXE
942 _cEBK
999 _c79587
_d79587