Graph Model For Conflict Resolution Research Articles

A Novel Consensus and Dissent Framework Under Grey Preference Based on the Graph Model for Conflict Resolution for Two Decision Makers

A Novel Consensus and Dissent Framework Under Grey Preference Based on the Graph Model for Conflict Resolution for Two Decision Makers

Conflict analysis of multiple decision-makers ecological environment governance of water resources based on graph model with heterogeneous preference in China's South-to-North water transfer project

Ecological environment governance of water resources is the foundation and key measures to ensure good water quality in China's South-to-North Water Transfer Project. However, as a limited rational economic person, considering their economic benefit, different involvers in China's South-to-North Water Transfer Project show different types of preference relations and make different action decisions as well as play conflicts with each other, which have a negative effect on ecological environmental governance. To overcome above-described shortcomings, heterogeneous preferences are integrated into graph model for conflict resolution (GMCR) to resolve ecological environment governance conflict of water resources. Specifically, first, four different structures of preference expression, including preference orderings, utility functions, multiplicative preferences, and additive preferences, are used to represent decision-maker's (DM's) preference information over states. Then, a novel preference ranking method is designed to calculate the ordinal preferences over all states by using matrix representation. Based on this, a set of heterogeneous stability definitions is proposed in GMCR to describe human diversified choice and behavior in detail, and it is applied to the ecological environment governance conflict of water resources in China's South-to-North Water Transfer Project. The heterogeneous stability analysis result showed that incentive policies used by water resources agencies can effectively encourage local governments and enterprises to actively participate in the ecological environment governance, and promote the ecological environment governance conflict to evolve into a state of equilibrium.

Grey preference for analyzing the influence of externality within the graph model for conflict resolution

Externality may have uncertain influence on decision makers (DMs). To address the conflicts with uncertain preference and externality, this study adopts the general grey number to measure the uncertain value of DMs’ option statements influenced by externality. It constructs adjustable grey preference influenced by externality (GPE), which can be dynamically adjusted according to the influence of externality. Subsequently, the study defines four equilibrium solutions for the graph model for conflict resolution based on grey preference influenced by externality (GPE-GMCR). Finally, the method is applied to a commercial bank operating conflict triggered by the Silicon Valley Bank (SVB) collapse in the United States, resulting in optimal results for conflict resolution. Specifically, the new model provides a practical tool for DMs, managers and policy makers to address conflicts arising from DMs’ uncertain preference under the influence of externality in complex environments.

Attitude-Based Intuitionistic Fuzzy Graph Model for Conflict Resolution With Soft Consensus: Application to Dam Construction Projects

Construction of dam projects built on international rivers usually faces many conflicts due to different interests, values, and preferences of social entities. The graph model for conflict resolution (GMCR) is a powerful and flexible tool to model and analyze strategic conflicts. In this study, we introduce a GMCR model to address construction conflicts among different social entities. To process uncertain and vague information in preferences, this study allows decision-makers to use intuitionistic fuzzy information to express their preference information. First, we define necessary definitions, including the intuitionistic relative certainty of preference (IRCP), intuitionistic satisficing threshold (IST), and intuitionistic unilateral improvement (IUI). When using a graph model to represent real-world disputes, a decision-maker (DM) may have different attitudes toward other DMs. To analyze the influence of attitudes, we originally introduced the concept of soft consensus in GMCR. Then, three kinds of attitudes, i.e., positive attitude, neutral attitude, and negative attitude, are identified. Next, we propose four intuitionistic stability definitions considering the attitudes of DMs. Finally, an illustrative example regarding the Xayaburi Dam dispute that occurred in Indochina Peninsula is provided to demonstrate the applicability of the proposed model.

Graph model for conflict resolution based on the combination of probabilistic uncertain linguistic and EDAS method

The ranking of decision makers (DMs)’ preferences for feasible states in the graph model for conflict resolution (GMCR) is crucial for accurately determining stability results. This paper addresses the issue of subjective ranking methods lacking theoretical foundation and causing ambiguity when the number of feasible states is high by proposing the implementation of the multi-attribute decision-making (MADM) method in the GMCR. The paper utilizes the average level to choose evaluation based on distance from average solution (EDAS) method for determining the DM’s preference ranking, which can effectively reduce the impact of anomalous evaluations. Further, the PUL-EDAS method based on probabilistic uncertainty linguistics (PUL) is developed, which overcomes the shortcomings of the traditional EDAS method, which only applies to the simple evaluation of information. The PUL aligns with DMs’ daily evaluation practice by providing an interval for the quality of qualitative linguistic evaluations. Furthermore, it utilizes an objective aggregation method to calculate comprehensive evaluation information from all DMs. In addition, the four fundamental stability definitions, applicable solely under crisp preferences, are extended to the PUL context, providing related extended definitions. Finally, to ensure the scientific validity and practicality of the proposed theory, this paper selects digital rural governance as the research context for conflict calculus analysis, comparing it with other MADM methods in the preference ranking section.

Matrix Representation and Behavioral Analysis in a Graph Model for Conflict Resolution With Incomplete Fuzzy Preferences

Matrix Representation and Behavioral Analysis in a Graph Model for Conflict Resolution With Incomplete Fuzzy Preferences

Minimax regret stability in the graph model for conflict resolution

In strategic conflicts, decision-makers (DMs) do not constantly make their best decisions, which makes room for DMs to feel regretful. In this context, this work proposes the Minimax Regret Stability within the graph model for conflict resolution (GMCR) for modelling and analysing conflicts, considering that DMs would feel regret for an unsatisfactory decision. This concept does not require knowledge about the opponent’s preference in bilateral conflicts. The aim of the new solution concept is to recommend a state as stable if there exists a policy recommending to stay at that state which minimizes the maximum regret of the DM for a given conflict horizon, where a policy specifies what action a DM must choose in every conflict state. In addition, we investigate the relations among the Minimax regret stability and other classical GMCR solution concepts. Following, the influence of the horizon on the stability of states is also studied. Finally, a truckers’ strike conflict was used to illustrate how the new solution concept can provide valuable strategic insights in real-life conflict situations.

E-Waste Management: An Analysis under the Perspective of Conflicts and Shared Responsibility

Background: The Brazilian National Solid Waste Policy establishes the shared responsibility of all actors involved in e-waste generation and management; however, some conflicts of interest need interventions and approaches for preventing them. Objective: This paper proposes using a graph model for conflict resolution (GMCR) decision support system to simulate the analysis and resolution of realistic e-waste management conflicts. Method: A systematic literature review focused on e-waste management, shared responsibility and conflict management was conducted, and a graph model for conflict resolution (GMCR) decision support system was applied to generate a framework to address this context. Results: The need for commitment agreements promoted by government institutions in partnerships with companies involved in the process is essential since the principle of shared responsibility requires educational actions, favoring efficiency in the reverse logistics recovery procedures for e-waste. Understanding the interconnected causes of conflicts and their facets is crucial for effective resolution and prevention, aiding comprehension, focused interventions, and evidence-based decision-making for transformative change amidst conflicting stakeholder objectives in the case of WEEE management. These results can be helpful for academics and practitioners working in this area.

First-level hypergame for investigating two decision-maker conflicts with unknown misperceptions of preferences within the framework of GMCR

Misunderstandings of preferences are ubiquitous in various types of conflicts, and such misperceptions often involve uncertainty due to the limited cognitive abilities and information asymmetry of decision-makers. This research proposes a novel hypergame analysis approach based on the graph model for conflict resolution to address challenging disputes involving unknown misunderstandings of preferences. Specifically, a first-level hypergame model with two decision-makers is intentionally developed in this study to handle the uncertainty of preference misunderstandings in conflicts. The logical definitions of stabilities in the first-level hypergame are put forward to portray various decision-making behaviors of stakeholders when facing the vagueness of preference misperceptions, and efficiently determine possible resolutions. Algebraic representations of stabilities are also designed for the first time to enhance the computational efficiency of hypergame analyses and facilitate the development of decision support systems. Furthermore, more general definitions of individual and overall equilibria and their algebraic representations are purposefully proposed within the first-level hypergame model. This allows the decision-makers involved in a conflict to hold stable under different solution concepts. Finally, this novel approach is applied to an environmental dispute to demonstrate its practicality in addressing real-world conflicts with uncertain misperceptions of preferences. The case study shows that the uncertainty of preference misunderstandings can affect the optimal strategy selections of decision-makers and result in changes to the equilibria or outcomes of conflicts.

Information asymmetry in the graph model of conflict resolution and its application to the sustainable water resource utilization conflict in Niangziguan Springs Basin

With the increasing consumption of global water resources, research on sustainable water resource utilization has become a topic of urgent interest. Despite the promulgation of policies and laws on the protection of water resources, the sustainable utilization and development of water resources in China are still far from reaching their initially established targets. This is partly explained by real-life conflicts that arise, in which different decision makers (DMs) possess different levels of professional knowledge, social status, and even power in contexts where the parties’ ability to leverage information varies greatly. Sustainable water resource utilization conflicts between the government and factories exemplify the impact of this information asymmetry on the relationship between DMs for the purposes of conflict resolution. In this paper, it is assumed that if one DM in a conflict has more information, their information advantage will affect the policy formation of the other DM. Thus, to analyze and resolve relevant problems, the concept of information asymmetry between two DMs is integrated into the basic structure of the graph model for conflict resolution (GMCR). According to the mathematical expression of the information asymmetry preferences of DMs, a set of information asymmetry stability definitions can be introduced to determine the stable state for each DM. The sustainable water resource utilization conflict in Niangziguan Springs Basin is used as an exemplar to confirm the effectiveness and correctness of the proposed method. Stability analysis shows that when the government implements strict environmental policies by leveraging more information, factories should adjust their preference relations to follow the rules and regulations to protect water resource in practice. Finally, comprehensive sustainable utilization and development of natural resource mechanisms must be implemented not only for these factories but also for other industries in China.

Matrix representations of the inverse problem in the graph model for conflict resolution with fuzzy preference

The inverse analysis of the graph model for conflict resolution (GMCR) determines all the preference relationships required by each decision-maker (DM) according to a given stability definition to ensure that the given state is stable. In the paper, a matrix representation approach for the inverse graph model with fuzzy preference relations is proposed to obtain all the preference relations for each DM making the stability result based on the fuzzy stability definition, including fuzzy Nash, fuzzy general metarationality, fuzzy symmetric metarationality, and fuzzy sequential stability definition. For the two-DM graph model, the fuzzy preference relation over states, unilateral movements, and fuzzy unilateral improvements are refreshed by using the matrix forms. Furthermore, for the multiple DMs model, the joint movements and joint improvement for a collection including at least two DM are represented by using matrix representation. Finally, the matrix relationship for specifying the required preference relation in the framework of inverse graph model with fuzzy preferences is derived. To illustrate the usefulness of the matrix representation of inverse graph model with fuzzy preference relations, this paper demonstrates it using a real-life conflict of the Elmira groundwater contamination conflict.

Matrix representations of berge stabilities in the graph model for conflict resolution

Matrix representations of berge stabilities in the graph model for conflict resolution

Conflict analysis based on a novel three-way decisions graph model for conflict resolution method under hesitant fuzzy environment

Multi-criteria decision aiding/making (MCDA/M) approach and three-way decisions (3WD) are embedded into the framework of graph model for conflict resolution (GMCR). The objective of this study is to develop more reasonable preference ranking for decision makers (DMs) produced from the perspective of options. This implies further simplification of the underlying computing behind conflict resolution. More specifically, DMs’ original option statements are evaluated by hesitant fuzzy sets (HFSs), then a three-way decisions approach is used to screen out the infeasible and rank the feasible option statements, and the feasible option statements’ loss values of three-way decisions approach are determined based on the hesitant fuzzy (HF) evaluation values. In addition, based on the value of conditional probability of the feasible option statements, an improved option prioritization technique with objective weights is developed to efficiently rank the conflict states, so that it can efficiently reflect the intensity of the ranking. Then, considering the preference thresholds of DMs, new definitions of threshold stabilities are proposed. As demonstrated by the case study in the problem of a carbon emission conflict in supply chain under “3060 carbon peak and neutrality” goal in China, the proposed novel three-way decisions graph model for conflict resolution (3WD-GMCR) framework can be widely applied to the realistic scenarios of decision-making. Compared with previous studies, the proposed approach can not only obtain the intensity ranking of conflict states, but also resolve complex large-scale conflicts effectively.

An Extension of Higher-Order Sequential Stabilities for Multilateral Conflicts and for Coalitional Analysis in the Graph Model for Conflict Resolution

An Extension of Higher-Order Sequential Stabilities for Multilateral Conflicts and for Coalitional Analysis in the Graph Model for Conflict Resolution

A novel grey-inverse graph model for conflict resolution approach for resolving water resources conflicts in the Poyang Lake Basin, China

With the continuous urbanization and industrialization in recent years, different stakeholders in the same basin meet local water needs and compete for water resources, which hinders economic development and ecological protection of the basin. Different stakeholders conceal information about their own strategies and preferences to protect their vested interests, making it difficult for third-party regulators to develop optimal operational policies for the joint use of water resources in the basin. Therefore, the research objective of this study is to propose a new grey inverse Graph Model for Conflict Resolution (grey inverse GMCR), and apply the new method to the complex problem of water allocation and environmental governance with the Poyang Lake basin conflict. The new GMCR model proposed in this study can solve the cost minimization problem of a third-party mediator that manipulates decision makers (DMs)’ grey preferences to achieve desired outcomes. The results of the equilibrium analysis show that upstream areas' preferences mainly affect the result of water resource conflicts in the PLB, and establishing a scientific mechanism to compensate the water resources protection cost borne by the upstream areas would be a cost-effective way to realize the sustainable development of the basin as a whole.

A Scientometric and Social Network Analysis of the Literature on the Graph Model for Conflict Resolution

A Scientometric and Social Network Analysis of the Literature on the Graph Model for Conflict Resolution

Development of a genetic algorithm-based graph model for conflict resolution for optimizing resolutions in environmental conflicts

Abstract Graph model for conflict resolution (GMCR) is a robust tool for resolving disagreements among parties with contradictory interests in a potential conflict. In GMCR, decision-makers (DMs) and their preferences are determined. The DMs are defined as people, parties, or groups having the authority to make decisions and the power to get these decisions approved. This definition excludes some potential stakeholders with no ability to make and exert decisions, like the natural environment. Therefore, this study aims to find an impartial viewpoint representing the natural environment's interests. A new GMCR based on genetic algorithm (GA) optimization is proposed to modify and optimize the final resolution of the GMCR regarding natural environment benefits. Having been applied to a real-world case study, this methodology showed competence in satisfying the fundamental interests of the natural environment to an acceptable extent. This case study is about an endangered seasonal lake, where there is contention between the governmental and agricultural sectors. The results revealed that the disagreement between two conflicting groups could be resolved by modifying the current agreement to consider both groups' demands. Finally, GA, incorporated in GMCR, proved to be a robust optimization technique in complex environmental conflicts.

A Graph Model for Conflict Resolution with Time-varying Attitudes and Its Application to China-US Trade Disputes

A Graph Model for Conflict Resolution with Time-varying Attitudes and Its Application to China-US Trade Disputes

Application of the graph model for conflict resolution in the truck driver strike in Brazil: a Case Study

One of the most stressful human interactions is conflict. In some cases, it can bring high losses even to parties that are not involved in the conflict. A possible scenario for resolving the conflict can be found using a Graph Model for Conflict Resolution (GMCR) which is a tool used to analyze conflicts and present scenarios that can be seen as possible solutions to the conflict. Considering several stability criteria, in this work, we present a case study: the historical background, the modeling using the GMCR and the stable states according to the presented criteria of a conflict that occurred in Brazil, where truck drivers went on strike and generated damages to the population such as a supply crisis (of food, medicines, fuel, among other products) and financial losses to the government (delay in the flow of goods, crowding of ports, among others), mainly in cities far from large urban centers and in centers for the flow of goods by road.

Belief-Based Preference Structure and Elicitation in the Graph Model for Conflict Resolution

A belief-based preference structure along with its associated elicitation approach is incorporated into the graph model for conflict resolution (GMCR) to model and analyze the multistakeholder strategic conflicts involving ambiguous evidences, incomplete information, and nonlinear causal relationships. More specifically, the relative preference is first redefined using a belief structure capable of capturing uncertainties of various types such as vagueness and/or ignorance in subjective judgments regarding the complex real-world conflicts. Next, a flexible and realistic methodology based on evidential reasoning is put forward to elicit the belief preference information over feasible states within the GMCR model. Then, 16 stability definitions (solution concepts) are extended to accommodate diverse uncertainties in preferences and facilitate the informed conflict analysis. The application and interpretation of the foregoing preference structure and associated stability definitions are demonstrated with an illustrative example.