000 04013nam a22005175i 4500
001 978-1-4419-1291-6
003 DE-He213
005 20140220084505.0
007 cr nn 008mamaa
008 100715s2010 xxu| s |||| 0|eng d
020 _a9781441912916
_9978-1-4419-1291-6
024 7 _a10.1007/978-1-4419-1291-6
_2doi
050 4 _aHD30.23
072 7 _aKJT
_2bicssc
072 7 _aKJMD
_2bicssc
072 7 _aBUS049000
_2bisacsh
082 0 4 _a658.40301
_223
100 1 _aMurty, Katta G.
_eauthor.
245 1 0 _aOptimization for Decision Making
_h[electronic resource] :
_bLinear and Quadratic Models /
_cby Katta G. Murty.
264 1 _aBoston, MA :
_bSpringer US :
_bImprint: Springer,
_c2010.
300 _aXXVI, 482p. 47 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aInternational Series in Operations Research & Management Science,
_x0884-8289 ;
_v137
505 0 _aLinear Equations, Inequalities, Linear Programming: A Brief Historical Overview -- Formulation Techniques Involving Transformations of Variables -- Intelligent Modeling Essential to Get Good Results -- Polyhedral Geometry -- Duality Theory and Optimality Conditions for LPs -- Revised Simplex Variants of the Primal and Dual Simplex Methods and Sensitivity Analysis -- Interior Point Methods for LP -- Sphere Methods for LP -- Quadratic Programming Models.
520 _aOptimization for Decision Making: Linear and Quadratic Models is a first-year graduate level text that illustrates how to formulate real world problems using linear and quadratic models; how to use efficient algorithms – both old and new – for solving these models; and how to draw useful conclusions and derive useful planning information from the output of these algorithms. While almost all the best known books on LP are essentially mathematics books with only very simple modeling examples, this book emphasizes the intelligent modeling of real world problems, and the author presents several illustrative examples and includes many exercises from a variety of application areas. Additionally, where other books on LP only discuss the simplex method, and perhaps existing interior point methods, this book also discusses a new method based on using the sphere which uses matrix inversion operations sparingly and may be well suited to solving large-scale LPs, as well as those that may not have the property of being very sparse. Individual chapters present a brief history of mathematical modeling; methods for formulating real world problems; three case studies that illustrate the need for intelligent modeling; classical theory of polyhedral geometry that plays an important part in the study of LP; duality theory, optimality conditions for LP, and marginal analysis; variants of the revised simplex method; interior point methods; sphere methods; and extensions of sphere method to convex and nonconvex quadratic programs and to 0-1 integer programs through quadratic formulations. End of chapter exercises are provided throughout, with additional exercises available online.
650 0 _aEconomics.
650 0 _aMathematical optimization.
650 0 _aIndustrial engineering.
650 0 _aOperations research.
650 1 4 _aEconomics/Management Science.
650 2 4 _aOperation Research/Decision Theory.
650 2 4 _aOperations Research, Management Science.
650 2 4 _aOptimization.
650 2 4 _aMathematical Modeling and Industrial Mathematics.
650 2 4 _aIndustrial and Production Engineering.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781441912909
830 0 _aInternational Series in Operations Research & Management Science,
_x0884-8289 ;
_v137
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-4419-1291-6
912 _aZDB-2-SBE
999 _c110364
_d110364