Asset Details
Do you wish to reserve the book?
A Novel Consensus and Dissent Framework Under Grey Preference Based on the Graph Model for Conflict Resolution for Two Decision Makers
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
A Novel Consensus and Dissent Framework Under Grey Preference Based on the Graph Model for Conflict Resolution for Two Decision Makers
Do you wish to request the book?
A Novel Consensus and Dissent Framework Under Grey Preference Based on the Graph Model for Conflict Resolution for Two Decision Makers
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
A Novel Consensus and Dissent Framework Under Grey Preference Based on the Graph Model for Conflict Resolution for Two Decision Makers
2024
Overview
The existing consensus models of conflict decision-making generally assume that the decision-makers’ preferences are simple and certain. This assumption oversimplifies the complexity of real-world conflicts due to the ignorance of the decision-maker’s limited rationality. The present work makes the first attempt at solving this issue by defining the grey consensus and dissent preference of two decision makers (DMs), which is then embedded into the Graph Model for Conflict Resolution (GMCR) to obtain conflict equilibrium solutions. To be specific, preference relations are first described as interval grey scales to reflect the decision maker’s judgments on conflict states, and then converted into crisp values to interface with GMCR. We next present both the logical and matrix representations under the GMCR framework, along with detailed pseudocode that can be implemented to investigate actual conflict situations practically. For validation and verification purposes, the proposed decision framework is applied to the water resource conflict of the Yellow River Basin in China, from which insights are derived to facilitate effective strategic decision-making for resolving complex conflicts in uncertain environments.
Publisher
Springer Nature B.V
Subject
