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035   $a(DE-He213)978-3-642-30504-7
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100   $a20120928d2013      u|         0
101 0 $aeng
135   $aur|n|---|||||
181   $ctxt
182   $cc
183   $acr
200 10$aHandbook of Optimization $eFrom Classical to Modern Approach /$fedited by Ivan Zelinka, Vaclav Snasael, Ajith Abraham
205   $a1st ed. 2013.
210  1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2013.
215   $a1 online resource (1087 p.)
225 1 $aIntelligent Systems Reference Library,$x1868-4394 ;$v38
300   $aDescription based upon print version of record.
311   $a3-642-30503-2 
320   $aIncludes bibliographical references and index.
327   $aClassical methods - theory -- Classical methods - Applications -- Heuristics - Theory -- Heuristics - Applications.
330   $aOptimization problems were and still are the focus of mathematics from antiquity to the present. Since the beginning of our civilization, the human race has had to confront numerous technological challenges, such as finding the optimal solution of various problems including control technologies, power sources construction, applications in economy, mechanical engineering and energy distribution amongst others. These examples encompass both ancient as well as modern technologies like the first electrical energy distribution network in USA etc. Some of the key principles formulated in the middle ages were done by Johannes Kepler (Problem of the wine barrels), Johan Bernoulli (brachystochrone problem), Leonhard Euler (Calculus of Variations), Lagrange (Principle multipliers), that were formulated primarily in the ancient world and are of a geometric nature. In the beginning of the modern era, works of L.V. Kantorovich and G.B. Dantzig (so-called linear programming) can be considered amongst others. This book discusses a wide spectrum of optimization methods from classical to modern, alike heuristics. Novel as well as classical techniques is also discussed in this book, including its mutual intersection. Together with many interesting chapters, a reader will also encounter various methods used for proposed optimization approaches, such as game theory and evolutionary algorithms or modelling of evolutionary algorithm dynamics like complex networks.  .
410  0$aIntelligent Systems Reference Library,$x1868-4394 ;$v38
606   $aComputational intelligence
606   $aArtificial intelligence
606   $aOperations research
606   $aDecision making
606   $aComputational Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/T11014
606   $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000
606   $aOperations Research/Decision Theory$3https://scigraph.springernature.com/ontologies/product-market-codes/521000
608   $aHandbooks and manuals.$2fast
615  0$aComputational intelligence.
615  0$aArtificial intelligence.
615  0$aOperations research.
615  0$aDecision making.
615 14$aComputational Intelligence.
615 24$aArtificial Intelligence.
615 24$aOperations Research/Decision Theory.
676   $a006.3
676   $a519.6
702   $aZelinka$b Ivan$4edt$4http://id.loc.gov/vocabulary/relators/edt
702   $aSnasael$b Vaclav$4edt$4http://id.loc.gov/vocabulary/relators/edt
702   $aAbraham$b Ajith$f1968-$4edt$4http://id.loc.gov/vocabulary/relators/edt
906   $aBOOK
912   $a9910438060203321
996   $aHandbook of Optimization$92546688
997   $aUNINA