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100   $a20180919d2018      u|         0
101 0 $aeng
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181   $ctxt$2rdacontent
182   $cc$2rdamedia
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200 10$aMultiple Criteria Decision Aid  $eMethods, Examples and Python Implementations /$fby Jason Papathanasiou, Nikolaos Ploskas
205   $a1st ed. 2018.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2018.
215   $a1 online resource (182 pages)
225 1 $aSpringer Optimization and Its Applications,$x1931-6836 ;$v136
311 08$a3-319-91646-7 
327   $a1. TOPSIS -- 2. VIKOR -- 3. PROMETHEE -- 4. SIR -- 5. AHP -- 6. Goal Programming.? Appendix.
330   $aMultiple criteria decision aid (MCDA) methods are illustrated in this book through theoretical and computational techniques utilizing Python. Existing methods are presented in detail with a step by step learning approach. Theoretical background is given for TOPSIS, VIKOR, PROMETHEE, SIR, AHP, goal programming, and their variations. Comprehensive numerical examples are also discussed for each method in conjunction with easy to follow Python code. Extensions to multiple criteria decision making algorithms such as fuzzy number theory and group decision making are introduced and implemented through Python as well. Readers will learn how to implement and use each method based on the problem, the available data, the stakeholders involved, and the various requirements needed. Focusing on the practical aspects of the multiple criteria decision making methodologies, this book is designed for researchers, practitioners and advanced graduate students in the applied mathematics, information systems, operations research and business administration disciplines, as well as other engineers and scientists oriented in interdisciplinary research. Readers will greatly benefit from this book by learning and applying various MCDM/A methods. (Adiel Teixeira de Almeida, CDSID-Center for Decision System and Information Development, Universidade Federal de Pernambuco, Recife, Brazil) Promoting the development and application of multicriteria decision aid is essential to ensure more ethical and sustainable decisions. This book is a great contribution to this objective. It is a perfect blend of theory and practice, providing potential users and researchers with the theoretical bases of some of the best-known methods as well as with the computing tools needed to practice, to compare and to put these methods to use. (Jean-Pierre Brans, Vrije Universiteit Brussel, Brussels, Belgium) This book is intended for researchers, practitioners and students alike in decision support who wish to familiarize themselves quickly and efficiently with multicriteria decision aiding algorithms. The proposed approach is original, as it presents a selection of methods from the theory to the practical implementation in Python, including a detailed example. This will certainly facilitate the learning of these techniques, and contribute to their effective dissemination in applications. (Patrick Meyer, IMT Atlantique, Lab-STICC, Univ. Bretagne Loire, Brest, France).
410  0$aSpringer Optimization and Its Applications,$x1931-6836 ;$v136
606   $aOperations research
606   $aManagement science
606   $aSoftware engineering
606   $aComputer software
606   $aComputer science?Mathematics
606   $aOperations Research, Management Science 
606   $aOperations Research and Decision Theory
606   $aSoftware Engineering
606   $aMathematical Software
606   $aMathematical Applications in Computer Science
615  0$aOperations research.
615  0$aManagement science.
615  0$aSoftware engineering.
615  0$aComputer software.
615  0$aComputer science?Mathematics.
615 14$aOperations Research, Management Science .
615 24$aOperations Research and Decision Theory.
615 24$aSoftware Engineering.
615 24$aMathematical Software.
615 24$aMathematical Applications in Computer Science.
676   $a005.133
700   $aPapathanasiou$b Jason$4aut$4http://id.loc.gov/vocabulary/relators/aut$0767853
702   $aPloskas$b Nikolaos$4aut$4http://id.loc.gov/vocabulary/relators/aut
906   $aBOOK
912   $a9910300139703321
996   $aMultiple Criteria Decision Aid$91923102
997   $aUNINA