TOPSIS and its Extensions: A Distance-Based MCDM Approach

Description

The objective of the book is to provide materials to demonstrate the development of TOPSIS and to serve as a handbook. It contains the basic process of TOPSIS, numerous variant processes, property explanations, theoretical developments, and illustrative examples with real-world cases. Possible readers would be graduate students, researchers, analysts, and professionals who are interested in TOPSIS, a distance-based algorithm, and who would like to compare TOPSIS with other MCDM methods. The book serves as a research reference as well as a self-learning book with step-by-step illustrations for the MCDM community. 498715_1_En_BookFrontmatter_OnlinePDF Preface Objective of the Study Book Organization Acknowledgements Contents About the Authors List of Figures 498715_1_En_1_Chapter_OnlinePDF 1 Multiple Criteria Modeling 1.1 Problems 1.2 Problem-Solving Process 1.3 Multiple Criteria Formulation 1.4 Alternatives 1.5 Solutions 1.6 Validation and Verification 1.7 Summary and Discussions References 498715_1_En_2_Chapter_OnlinePDF 2 TOPSIS Basics 2.1 Origin, Benefits, and Drawbacks 2.2 TOPSIS Algorithm 2.3 TOPSIS Choice Behavior 2.4 TOPSIS Inputs 2.5 Current Developments 2.6 Illustrative Example: A Recruitment and Selection Problem 2.7 Summary and Discussions References 498715_1_En_3_Chapter_OnlinePDF 3 TOPSIS Variants 3.1 Normalization Process 3.2 Weights for Aggregation 3.3 Distance Functions 3.4 Selection on PIS/NIS 3.5 Relative Closeness Formula 3.6 Ordinal Input 3.7 Weights on Separation Measures 3.8 Dependent Criteria 3.8.1 ANP Concept 3.8.2 Mahalanobis Distance 3.8.3 Other Approaches 3.9 Incremental Analysis 3.10 Summary and Discussions References 498715_1_En_4_Chapter_OnlinePDF 4 Group Aspects of TOPSIS 4.1 Backgrounds of Group Decisions 4.2 Group Decision Processes 4.3 Consensus in Group TOPSIS 4.3.1 Consensus Measures and Reaching 4.3.2 Consensus Reaching Process 4.3.3 Ngwenyama et al.’s Approach 4.3.4 Madu’s Approach 4.4 Consensus on Thresholds 4.5 Summary and Discussions Appendix A References 498715_1_En_5_Chapter_OnlinePDF 5 TOPSIS for Decision Support 5.1 Necessity of Decision Support 5.2 DSS Configurations and Components 5.2.1 DSSs and GDSSs 5.2.2 TOPSIS’s Components 5.3 TOPSIS-Supported DSS Applications 5.3.1 Manufacturing Location Selection GDSS 5.3.2 Product Development DSS 5.3.3 Recruitment and Selection GDSS 5.3.4 Investment Evaluation DSS 5.3.5 Green Product Design DSS 5.3.6 Closed-Loop Supply Chain Network Design DSS 5.3.7 Customer-Driven Product Design DSS 5.3.8 Manufacturing System Reconfiguration DSS 5.3.9 Food Supply Chains DSS 5.3.10 Safety Inspection DSS 5.3.11 Automobile Components Procurement DSS 5.4 Summary and Discussions References 498715_1_En_6_Chapter_OnlinePDF 6 Sorting Problems by TOPSIS 6.1 TOPSIS for Sorting 6.2 Proposed Sorting Approach 6.2.1 Determination of Cut-Off Values 6.2.2 Suggested Sorting Procedure 6.3 Analytic Results 6.3.1 Case Background 6.3.2 Comparative Results 6.4 Summary and Discussions References 498715_1_En_7_Chapter_OnlinePDF 7 Rank Reversal in TOPSIS 7.1 Rank Reversal 7.2 TOPSIS Rank Reversal 7.3 Illustrative Examples 7.4 Theoretical Insights 7.5 Summary and Discussions References 498715_1_En_8_Chapter_OnlinePDF 8 Other Related Methods 8.1 Fuzzy TOPSIS 8.1.1 Fuzzy Numbers 8.1.2 Fuzzy Operations 8.1.3 Fuzzy TOPSIS Approach 8.1.4 Choquet Integral for TOPSIS 8.2 VIKOR 8.3 BWM 8.4 Summary and Discussions References 498715_1_En_9_Chapter_OnlinePDF 9 TOPSIS Applications 9.1 Selection Applications 9.1.1 Location Decisions 9.1.2 Selection Decisions 9.1.3 Other Applications 9.2 Assessment Applications 9.3 Group Applications 9.3.1 Effectiveness 9.4 Conclusions References 498715_1_En_BookBackmatter_OnlinePDF Index