Zopounidis / Doumpos Multiple Criteria Decision Making

Applications in Management and Engineering
1. Auflage 2017
ISBN: 978-3-319-39292-9
Verlag: Springer Nature Switzerland
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 218 Seiten

Reihe: Multiple Criteria Decision Making

This book presents a broad range of innovative applications and case studies in all areas of management and engineering, including public administration, finance, marketing, engineering, transportation, and energy systems. It addresses issues related to problem structuring, preference modeling, and model construction, presenting a framework that provides clear decision-making support in practice. In addition, it includes hybrid and integrated techniques combining multiple criteria decision making (MCDM) with other analytical methods. The book reflects the growing impact of MCDM in the field of management science and operations research. Building on recent and established theoretical advances and presenting their applications in specific domains, it offers a comprehensive resource for researchers, graduate students and professionals alike. 

Constantin Zopounidis is Professor of Financial Engineering and Operations Research, at Technical University of Crete (Greece), Distinguished Research Professor in Audencia Nantes, School of Management (France), and Senior Academician of the Royal Academy of Economics and Financial Sciences of Spain. His research interests include financial engineering, financial risk management, and multiple criteria decision making. He has published over 300 papers in premier international journals, edited volumes, and conference proceedings. He has also published several books and edited volumes on multicriteria decision making, financial engineering, and operations research. Prof. Zopounidis is Editor-in-Chief and member of the editorial board of several international journals. For his research work, Prof. Zopounidis has received awards and honorary distinctions from international research organizations, including among others the ??ISIL International Foundation, the Decision Sciences Institute, the European Association of Management and Business Economics, the Royal Academy of Doctors of Spain, the Hellenic Operational Research Society, and the International Association for Fuzzy Set Management and Economy. In 2013 he was the recipient of the MCDM Edgeworth-Pareto Award of the International MCDM Society. 

Michael Doumpos holds a PhD in operations research (2000) and a MSc in Production Engineering and Management (1997) from the Technical University of Crete, where he currently holds an Assistant Professor position. His research interests include multiple criteria decision making, decision support systems, computational pattern recognition and financial risk management. He has published over 50 research articles in premier international journals. He has also co-authored several books, edited volumes, book chapters, conference papers and edited special issues. Prof. Doumpos is associate editor of OMEGA and recipient of the best reviewer award from the European Journal of Operational Research (2010 and 2012). 

Autoren/Hrsg.

Zopounidis, Constantin

Doumpos, Michael

Inhaltsverzeichnis

1;Preface;6
1.1;Introduction to the Theme of the Book;6
1.2;Outline of the Book;7
1.3;Acknowledgments;9
2;Contents;10
3;Contributors;12
4;1 Decision Aid in Public Administration: From Evidence-Based Decision Making to OrganizationalLearning;14
4.1;1.1 Introduction;14
4.2;1.2 Complexity Elements and Challenges;16
4.2.1;1.2.1 MCDA in Complex Situations;18
4.2.2;1.2.2 MC Applications Without the Activation of a Decision System;20
4.2.3;1.2.3 Decision System Open to Participation;22
4.2.4;1.2.4 Internal PA Decision System and Process;24
4.3;1.3 A Framework to Underline the Main Aspects of an MC Application in PA;26
4.3.1;1.3.1 Prioritization of Public Investments in Social Infra-Structures Using Multicriteria Value Analysis and Decision Conferencing [6];29
4.3.2;1.3.2 An MC Application in the Sustainable Energy Action Plan Ambit [18];30
4.3.3;1.3.3 An MC Approach for the Concept Design of a Complex Project [58, 59];32
4.3.4;1.3.4 A Knowledge Base and an ELECTRE Tri Application to Facilitate New Financing Actions in the Public Sector [56];34
4.4;1.4 Conclusions;36
4.5;References;38
5;2 Measuring Social Responsibility: A Multicriteria Approach;43
5.1;2.1 Introduction;43
5.2;2.2 Measuring the Social Responsibility of an Investment;45
5.3;2.3 Portfolio Selection Model for Socially Responsible Investment;53
5.3.1;2.3.1 Methodology;53
5.3.2;2.3.2 Results;54
5.4;2.4 Conclusions;56
5.5;References;57
6;3 Multi-Criteria Decision Analysis for Financial Investments Using AHP;59
6.1;3.1 Introduction: Banking and Microfinance Institution;59
6.2;3.2 Presentation of the AHP Method;60
6.3;3.3 Financial Institutions Definition;61
6.3.1;3.3.1 Analysis and Identification of the Project Objective;61
6.3.2;3.3.2 Develop the Hierarchical Structure of the Project: Risk Definition;62
6.4;3.4 Financial Institutions Analysis Step by Step;62
6.4.1;3.4.1 The Hierarchical Structure;62
6.4.2;3.4.2 Pairwise Comparisons for Criteria;64
6.4.3;3.4.3 Comparison Judgment Matrix;65
6.4.4;3.4.4 Priority Vector Calculation;66
6.4.5;3.4.5 Calculation of the Value ?max;66
6.4.6;3.4.6 Determine the Value of Random Index (RI);67
6.4.7;3.4.7 Calculation of Consistency Index: CI;68
6.4.8;3.4.8 Consistency Ratio Calculation (CR);68
6.4.9;3.4.9 Establish the Full Table of Criteria Comparison;68
6.4.10;3.4.10 Determine the Relative Importance of Criteria;69
6.4.11;3.4.11 Project Aggregation Calculation;69
6.4.12;3.4.12 Establish Comparisons by Pair of Studied Alternatives;69
6.4.13;3.4.13 Determine the Performance of the Alternatives Relatively to the Sub-Criteria;73
6.4.14;3.4.14 Calculation of the Final Aggregation;73
6.5;3.5 Conclusions and Perspectives;79
6.6;References;79
7;4 Financing Innovative SMEs;80
7.1;4.1 Introduction;80
7.2;4.2 A Brief Reminder of ELECTRE TRI and SMAA-TRI;81
7.2.1;4.2.1 ELECTRE TRI;81
7.2.2;4.2.2 SMAA-TRI;83
7.3;4.3 A Brief Introduction to the Multicriteria Judgemental Rating Model;83
7.3.1;4.3.1 Selection of the Evaluation Criteria;84
7.3.2;4.3.2 Definition of the Risk Classes;84
7.3.3;4.3.3 Assessment of the Criteria Weights;84
7.4;4.4 Case Study;86
7.5;References;91
8;5 A Multi-Criteria Recommender System Based on Users' Profile Management;93
8.1;5.1 Introduction;93
8.2;5.2 Recommenders Systems;94
8.3;5.3 Multi-Criteria Decision Support;95
8.4;5.4 Machine Learning;97
8.5;5.5 System Description;98
8.6;5.6 System Operating;99
8.6.1;5.6.1 Introduction;99
8.6.2;5.6.2 Scoring;100
8.6.3;5.6.3 Rate Computation;100
8.6.4;5.6.4 Pairwise Computation;101
8.7;5.7 Experiments and Results;103
8.8;5.8 Conclusions and Perspectives;106
8.9;References;107
9;6 E-commerce in the Context of Protected Areas Development: A Managerial Perspective Under a Multi-Criteria Approach;109
9.1;6.1 Introduction;110
9.2;6.2 Data and Methodology;112
9.2.1;6.2.1 Data;112
9.2.2;6.2.2 Methodology;112
9.3;6.3 Results and Discussion;117
9.4;6.4 Conclusions;119
9.5;References;119
10;7 Solving a Multicriteria Road Design Problem:A Practical Example;122
10.1;7.1 Introduction;122
10.2;7.2 Research Motivation;125
10.2.1;7.2.1 An Innovative Approach of Road Design;125
10.2.1.1;7.2.1.1 For a Preventive Assessment of Road Safety;125
10.2.1.2;7.2.1.2 A Support to Sustainable Road Projects;127
10.2.2;7.2.2 Towards a Multicriteria Analysis of the Design Process;128
10.3;7.3 Methodology;129
10.3.1;7.3.1 Multiobjective Evolutionary Algorithm;129
10.3.2;7.3.2 Multicriteria Ordered Clustering Model;131
10.3.2.1;7.3.2.1 The PROMETHEE Methods;131
10.3.2.2;7.3.2.2 The FlowSort Method;133
10.3.2.3;7.3.2.3 The PCLUST Model;133
10.4;7.4 Case Study: A Rural Road Project in Belgium;135
10.4.1;7.4.1 Definition of the Problem;136
10.4.2;7.4.2 Identifying the Approximated Set of Performing Solutions;137
10.4.3;7.4.3 Solving the Multicriteria Decision Problem;139
10.5;7.5 Conclusions;141
10.6;References;143
11;8 Locating Ship-to-Ship (STS) Transfer Operations via Multi-Criteria Decision Analysis (MCDA): A Case Study;146
11.1;8.1 Introduction;147
11.2;8.2 The Role of STS Transfer Areas;149
11.3;8.3 The ELECTRE Methodology;150
11.4;8.4 STS Location Problem Definition;151
11.4.1;8.4.1 Introduction to the Transfer Areas;151
11.4.2;8.4.2 Addressing a Consistent Family of Criteria;152
11.5;8.5 Results;157
11.5.1;8.5.1 Weight Determination;157
11.5.2;8.5.2 Veto Threshold Determination;160
11.5.3;8.5.3 Concordance Analysis;160
11.5.4;8.5.4 Discordance Analysis;161
11.5.5;8.5.5 The Kernel of the Outranking Graph;162
11.6;8.6 Discussion;162
11.6.1;8.6.1 Robustness Analysis of Criteria Weights;162
11.6.2;8.6.2 Interpretation of the Results;163
11.7;8.7 Conclusion;164
11.8;Appendix 1: Analytical Description of the ELECTRE I Methodology;165
11.9;Appendix 2: Short Introduction to the Proposed STS Transfer Locations;167
11.10;Appendix 3: Main Characteristics of the Vessel Used in the Practical Example;170
11.11;References;170
12;9 MCDM Applied to the Partitioning Problem of 3D-Stacked Integrated Circuits;173
12.1;9.1 Introduction;174
12.2;9.2 Multi-Criteria Decision Making Tools: The PROMETHEE Methods;176
12.3;9.3 3D Integration Technology;178
12.3.1;9.3.1 Implementation;180
12.4;9.4 Case Study;184
12.4.1;9.4.1 Experimental Set-up: Design and Implementation;184
12.4.2;9.4.2 Multi-Criteria Analysis;184
12.4.2.1;9.4.2.1 High Performance Production Scenario;185
12.4.2.2;9.4.2.2 Low Cost Production Scenario;188
12.4.2.3;9.4.2.3 Results Interpretation for an IC Designer;191
12.5;9.5 Conclusion and Future Works;192
12.6;Appendix;193
12.7;OpenSPARC-T2 SoC Design Alternatives: Evaluation Table;193
12.8;References;195
13;10 A MCDA-Based Approach for Evaluating Alternative Requalification Strategies for a Net-Zero Energy District (NZED);196
13.1;10.1 Introduction;197
13.2;10.2 Methodological Framework;198
13.3;10.3 Application;200
13.3.1;10.3.1 Description of the Case Study;200
13.3.2;10.3.2 Presentation of the Alternative Strategies for Energy Requalification;202
13.3.3;10.3.3 Definition and Evaluation of the Criteria;203
13.3.3.1;10.3.3.1 Energy Performance;204
13.3.3.2;10.3.3.2 CO2 Emissions;204
13.3.3.3;10.3.3.3 Global Cost;205
13.3.3.4;10.3.3.4 Indoor Comfort;206
13.3.3.5;10.3.3.5 Energy Surplus Production;206
13.3.3.6;10.3.3.6 Green Jobs;206
13.3.3.7;10.3.3.7 Real Estate Market Value;207
13.3.3.8;10.3.3.8 Construction of the Performance Matrix;208
13.3.4;10.3.4 Weighting;209
13.3.5;10.3.5 Aggregation;210
13.4;10.4 Discussion of the Results;211
13.5;10.5 Conclusions;214
13.6;References;216