國立虎尾科技大學 |

Multiple Criteria Decision Aid = Methods, Examples and Python Implementations /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Multiple Criteria Decision Aid / by Jason Papathanasiou, Nikolaos Ploskas.
Reminder of title:	Methods, Examples and Python Implementations /
Author:	Papathanasiou, Jason.
other author:	Ploskas, Nikolaos.
Description:	XVII, 173 p. 36 illus., 18 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Operations research. -
Online resource:	https://doi.org/10.1007/978-3-319-91648-4
ISBN:	9783319916484

Multiple Criteria Decision Aid = Methods, Examples and Python Implementations /
Papathanasiou, Jason.

Multiple Criteria Decision Aid Methods, Examples and Python Implementations /[electronic resource] :by Jason Papathanasiou, Nikolaos Ploskas. - 1st ed. 2018. - XVII, 173 p. 36 illus., 18 illus. in color.online resource. - Springer Optimization and Its Applications,1361931-6828 ;. - Springer Optimization and Its Applications,104.

1. TOPSIS -- 2. VIKOR -- 3. PROMETHEE -- 4. SIR -- 5. AHP -- 6. Goal Programming.– Appendix.

Multiple 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).

ISBN: 9783319916484

Standard No.: 10.1007/978-3-319-91648-4doiSubjects--Topical Terms:

573517
Operations research.

LC Class. No.: QA402-402.37

Dewey Class. No.: 519.6

Multiple Criteria Decision Aid = Methods, Examples and Python Implementations /
LDR:04096nam a22004335i 4500 001 991724
003 DE-He213
005 20200704120145.0
007 cr nn 008mamaa
008 201225s2018 gw | s |||| 0|eng d
020 $a 9783319916484 $9 978-3-319-91648-4
024 7 $a 10.1007/978-3-319-91648-4 $2 doi
035 $a 978-3-319-91648-4
050 4 $a QA402-402.37
050 4 $a T57.6-57.97
072 7 $a KJT $2 bicssc
072 7 $a BUS049000 $2 bisacsh
072 7 $a KJT $2 thema
072 7 $a KJM $2 thema
082 0 4 $a 519.6 $2 23
100 1 $a Papathanasiou, Jason. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1116255
245 1 0 $a Multiple Criteria Decision Aid $h [electronic resource] : $b Methods, Examples and Python Implementations / $c by Jason Papathanasiou, Nikolaos Ploskas.
250 $a 1st ed. 2018.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2018.
300 $a XVII, 173 p. 36 illus., 18 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a Springer Optimization and Its Applications, $x 1931-6828 ; $v 136
505 0 $a 1. TOPSIS -- 2. VIKOR -- 3. PROMETHEE -- 4. SIR -- 5. AHP -- 6. Goal Programming.– Appendix.
520 $a Multiple 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).
650 0 $a Operations research. $3 573517
650 0 $a Management science. $3 719678
650 0 $a Decision making. $3 528319
650 0 $a Software engineering. $3 562952
650 0 $a Computer software. $3 528062
650 0 $a Computer science—Mathematics. $3 1253519
650 0 $a Computer mathematics. $3 1199796
650 1 4 $a Operations Research, Management Science. $3 785065
650 2 4 $a Operations Research/Decision Theory. $3 669176
650 2 4 $a Software Engineering/Programming and Operating Systems. $3 669780
650 2 4 $a Mathematical Software. $3 672446
650 2 4 $a Mathematical Applications in Computer Science. $3 815331
700 1 $a Ploskas, Nikolaos. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1116256
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783319916460
776 0 8 $i Printed edition: $z 9783319916477
776 0 8 $i Printed edition: $z 9783030062729
830 0 $a Springer Optimization and Its Applications, $x 1931-6828 ; $v 104 $3 1255232
856 4 0 $u https://doi.org/10.1007/978-3-319-91648-4
912 $a ZDB-2-SMA
912 $a ZDB-2-SXMS
950 $a Mathematics and Statistics (SpringerNature-11649)
950 $a Mathematics and Statistics (R0) (SpringerNature-43713)