Consensus Building in Group Decision Making

Searching the Consensus Path with Minimum Adjustments

AvYucheng Dong,Jiuping Xu

Inbunden, Engelska, 2015

573 kr

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Häftad

573 kr

Beskrivning

This book is intended for researchers and postgraduates who are interested in the consensus reaching process in group decision-making problems. It puts forward new optimization-based decision support approaches to help decision-makers find roadmaps to consensus with minimum adjustments. Simulation experiments and comparison analysis are subsequently conducted to assess the validity of the proposal. After reading this book, readers will possess a number of valuable tools for building consensus with minimum adjustments in the context of group decision-making. Further, the proposed approach can effectively reduce costs in consensus building.

Produktinformation

Utgivningsdatum:2015-10-30
Mått:155 x 235 x 17 mm
Vikt:534 g
Format:Inbunden
Språk:Engelska
Antal sidor:201
Upplaga:15001
Förlag:Springer Verlag, Singapore
ISBN:9789812878908

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Mer om författaren

Yucheng Dong is a Professor with the Business School of Sichuan University, China. His research interests include group decision making, consensus reaching process, and computing with words in decision making. He is the author or coauthor of over 50 refereed articles published in international journal including Decision Support Systems, European Journal of Operational Research, Group Decision and Negotiation, IEEE Transactions (TFS, SMC, TYB), Information Sciences, and Knowledge-based Systems, among others. Several of his papers (currently 4) are classed as highly cited by ISI

Innehållsförteckning

Preface.- Part I: Introduction.- Group decision making.- Consensus reaching process.- Part II: Consensus models with the minimum adjustments and aggregation operators.- Minimum adjustments consensus models.- Maximum expert consensus models.- Part III: Consensus in the multiple attribute group decision making.- Consensus rule I: minimizing the distance between original and adjusted preferences.- Consensus rule II: minimizing the number of adjusted preference values.- Interactive multiple attribute consensus framework to support consensus reaching.- Part IV: Consensus in the group decision making with preference relations.- Individual consistency issues in preference relations.- Consensus framework with minimum adjustments to integrate the individual consistency.- Part V: Consensus in the linguistic group decision making.- Linguistic consensus model with minimum adjustments.- Minimizing adjusted simple terms in the hesitant linguistic consensus reaching.- Part VI: Simulation experiments and comparison analysis.- Simulation experiments and comparison analysis.- Appendix.

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Distributed Computing and Artificial Intelligence, 17th International Conference

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