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008 100316s2010 xxu| s |||| 0|eng d
020 _a9781441957719
_9978-1-4419-5771-9
040 _cMX-MeUAM
050 4 _aHD30.23
082 0 4 _a658.40301
_223
100 1 _aJones, Dylan.
_eauthor.
245 1 0 _aPractical Goal Programming
_h[recurso electrónico] /
_cby Dylan Jones, Mehrdad Tamiz.
250 _a1.
264 1 _aBoston, MA :
_bSpringer US,
_c2010.
300 _aXIV, 238p. 82 illus., 41 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 _aInternational Series in Operations Research & Management Science,
_x0884-8289 ;
_v141
505 0 _aHistory and Philosophy of Goal Programming -- Goal Programming Variants -- Formulating Goal Programmes -- Advanced Topics in Goal Programming Formulation -- Solving and Analysing Goal Programming Models -- Detection and Restoration of Pareto Inefficiency -- Trend of Integration and Combination of Goal Programming -- Case Study: Application of Goal Programming in Health Care -- Case Study: Application of Goal Programming in Portfolio Selection.
520 _aPractical Goal Programming is intended to allow academics and practitioners to be able to build effective goal programming models, to detail the current state of the art, and to lay the foundation for its future development and continued application to new and varied fields. Suitable as both a text and reference, its nine chapters first provide a brief history, fundamental definitions, and underlying philosophies, and then detail the goal programming variants and define them algebraically. Chapter 3 details the step-by-step formulation of the basic goal programming model, and Chapter 4 explores more advanced modeling issues and highlights some recently proposed extensions. Chapter 5 then details the solution methodologies of goal programming, concentrating on computerized solution by the Excel Solver and LINGO packages for each of the three main variants, and includes a discussion of the viability of the use of specialized goal programming packages. Chapter 6 discusses the linkages between Pareto Efficiency and goal programming. Chapters 3 to 6 are supported by a set of ten exercises, and an Excel spreadsheet giving the basic solution of each example is available at an accompanying website. Chapter 7 details the current state of the art in terms of the integration of goal programming with other techniques, and the text concludes with two case studies which were chosen to demonstrate the application of goal programming in practice and to illustrate the principles developed in Chapters 1 to 7. Chapter 8 details an application in healthcare, and Chapter 9 describes applications in portfolio selection.
650 0 _aEconomics.
650 0 _aMathematical optimization.
650 0 _aOperations research.
650 1 4 _aEconomics/Management Science.
650 2 4 _aOperations Research/Decision Theory.
650 2 4 _aOptimization.
650 2 4 _aMathematical Modeling and Industrial Mathematics.
650 2 4 _aOperations Research, Mathematical Programming.
700 1 _aTamiz, Mehrdad.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781441957702
830 0 _aInternational Series in Operations Research & Management Science,
_x0884-8289 ;
_v141
856 4 0 _zLibro electrónico
_uhttp://148.231.10.114:2048/login?url=http://link.springer.com/book/10.1007/978-1-4419-5771-9
596 _a19
942 _cLIBRO_ELEC
999 _c199379
_d199379