Fuzzy Social Choice Research Articles

Assessing the Uncertainty of Hydropower-Environmental Conflict-Resolution Management under Climate Change

To balance the water demands of different departments and produce a win–win result for reservoir operation, a series of conflict-resolution methods have been developed to define the socio-optimal operation strategy for specific conflict problems. However, given the inherent uncertainty of reservoir operation brought by climate change, the compromised strategies selected by conflict-resolution methods can vary. Therefore, quantifying the impacts of climate change on the decision characteristics of conflict-resolution methods can help to address questions about whether conflict-resolution decisions are sustainable given unforeseen changes. In this study, the Yangtze River is regarded as study area. As a world-class hydropower project located on the midstream of Yangtze River, Three Gorges Hydroelectric Power Station can transfer plenty of water energy into electricity. To alleviate the ecological water shortage caused by hydropower operation, sustainable and balanced operation strategies considering the water demands of two departments needs to be studied. In the context of hydropower-environmental conflict-resolution management, the decision behaviors of two fuzzy social choice methods and four game-theoretical bargaining methods under 25 kinds of future climate scenarios are analyzed. Comparing the strategy selection results of different methods for a future period (2021–2082) shows that in all proposed climate scenarios, the decisions of the Nash bargaining method, alternating offer method, and unanimity fallback bargaining method in game-theoretical bargaining methods are more stable than other studied methods, which means that climate change affects the decision behaviors of these three methods slightly. In addition, balanced strategies selected by these three methods could formulate adaptable reservoir operation policies that would satisfy the interests of hydropower and environmental stakeholders equally, and avoid a very low satisfaction level of individual stakeholder and whole stakeholders in the water-conflict year. Therefore, against the background of an increasing demand for environmental protection, these three methods can provide socio-optimal strategies considering social and economic benefits for water resource management.

Multi-objective decision-making for green infrastructure planning (LID-BMPs) in urban storm water management under uncertainty

Sustainable urban surface runoff management is receiving increased attention due to environmental and ecological consequences related to urbanization. This study presents a useful new framework for green infrastructure (GI) planning for the management of urban runoff quality and quantity. The proposed framework considers physical, technical, economic, and multi-stakeholder aspects related to urban runoff management while simultaneously addressing the uncertainties of the decision-making process and model parameters. The methodology is applied to regionally locating and sizing low impact development-best management practices (LID-BMPs) while considering the hydrologic and hydraulic impacts. A decision-making multi-objective optimization framework is developed by integrating: 1) a Multi-Layer Perceptron neural network founded on a Storm Water Management Model (SWMM-MLP meta-model), 2) NSGA-II multi-objective optimization, 3) fuzzy α-cut technique, and 4) a decision-making support model based on social choice theory to elicit trade-offs among system cost and LID-BMP performance indicators. The decision-making model, based on Fuzzy Social Choice (FSC) theory, is applied to simulate consensus between stakeholders for a partially cooperative group decision-making problem. The proposed methodology is explored in a catchment located in the northeastern part of Tehran, Iran. Results showed that the SWMM could be effectively replaced with a MLP-based meta-model in simulation-optimization problems for urban runoff management. In the application of FSC methods, the optimal scenarios were effective in reducing the volume of urban runoff and contamination loads while maintaining the optimality of the operation costs. Considering the optimal LID scenario, a reduction of more than 99% in runoff volume and biochemical oxygen demand (BOD), and a decrease of more than 92% of total suspended solids (TSS), occurred for the lower bound of uncertainty (lower (left) end of the α-cut = 0.3). For the upper bound of uncertainty (upper (right) end of the α-cut level = 0.3), a maximum reduction of 57% was obtained. In applying FSC methods through the decision-making process, the Borda Counting method considered the preferences of all stakeholders best. Moreover, the proposed framework allows decision-makers to decide on the acceptability and reliability of the optimal management scenarios considering their preferences and uncertainties.

Analyzing the Impacts of Climate Change on Hydro-Environmental Conflict-Resolution Management

Conflict-resolution methods have been applied to water resources management to balance conflicting interests of stakeholders. Due to the climate change impacts on hydrologic processes, the strategy selections of conflict-resolution methods can be influenced, resulting in different selection rules for historical and future periods. This study aims to quantify the impacts of climate change on the strategy-selection rules of the conflict-resolution methods for better long-term strategic decision-making. The methodology of this study consists of climatic, hydrological, environmental and multi-objective optimization models, two fuzzy social choice methods (FSCMs) and four game-theoretical bargaining methods (GTBMs). The hydro-environmental conflict-resolution management in the Yangtze River of China is selected as the case study. The results show that the strategy selection of GTBMs is more stable and results in a better balance between hydropower and environmental objectives, compared to that of FSCMs. Moreover, considering climate change, under the appropriate environmental flow pattern, the stabilities of the strategy selections of FSCMs and GTBMs are slightly influenced, and the average satisfied degrees of both objectives obtained by FSCMs and GTBMs in the future period (2021-2080) are lower than those in the base period (1950-2012). The findings from this study provide guidance for hydro-environmental conflict-resolution management from a sustainable development perspective.

An Entropy-Based Approach to Fuzzy Multi-objective Optimization of Reservoir Water Quality Monitoring Networks Considering Uncertainties

In this study, a new fuzzy methodology for a multi-objective optimization of reservoir Water Quality Monitoring Stations (WQMS) was developed, based on Transinformation Entropy (TE), the IRanian Water Quality Index (IRWQI), and fuzzy social choice considering uncertainties. The approach was utilized in the Karkheh Dam reservoir in Iran. The objective functions were: 1) minimizing costs, 2) minimizing redundant information and uncertainties, and 3) maximizing the spatial coverage of the network. A CE-QUAL-W2 model was used for the simulation of water quality variables. The IRWQI was computed to reveal a complete picture of the reservoir water quality. The TE quantities were calculated for each pair of potential stations. The TE values were plotted against the spatial distances among potential WQMS to obtain the TE–Distance (TE–D) curve, and minimize redundant information among stations, while providing coverage of the entire network. A multi-objective Genetic Algorithm (NSGA-II) was applied to obtain Pareto-optimal solutions taking stakeholder preference into account. The most preferred solution was then obtained using fuzzy social choice approaches to achieve a consensus. The fuzziness embedded in the decision-making procedure, the uncertainty in the value of mutual information, and the uncertainty in identifying the optimal distance among WQMS were also investigated. Results indicated that the three fuzzy social choice approaches (Borda Count, Minimax, and Approval Voting) led to the same number of optimized WQMS in each fuzzy alpha-cut. Based on the fuzzy linguistic quantifiers method, the number of optimized WQMS was increased.

A fuzzy multi-stakeholder multi-criteria methodology for water allocation and reuse in metropolitan areas.

In this paper, a fuzzy decision making methodology is proposed to find a socially optimal scenario for allocating effluent of wastewater treatment plants and urban and suburban runoffs to agricultural regions and recharging aquifers. The presented methodology named modified fuzzy social choice (MFSC) considers multi-stakeholder multi-criteria problems under uncertainties inherent in a decision making process utilizing a fuzzy ranking method and the fuzzy social choice (FSC) theory. A set of water and wastewater allocation scenarios are proposed for water quantity and quality management of the study area, while six main stakeholders with conflicting utilities and different negotiation powers are involved. The proposed methodology is applied to Tehran metropolitan area, the capital city of Iran with the population of about 8 million people, to examine its applicability and effectiveness. The results shows that using fuzzy multi-stakeholder multi-criteria decision making method considering equal and different negotiation powers can lead to different outcomes. Based on the results, the MFSC method, which considers a number of decision makers having different negotiation powers, degrees of importance of decision making criteria, and some important uncertainties, performs more promising in real water resources management problems.

Hydro-environmental management of groundwater resources: A fuzzy-based multi-objective compromise approach

Sustainable management of water resources necessitates close attention to social, economic and environmental aspects such as water quality and quantity concerns and potential conflicts. This study presents a new fuzzy-based multi-objective compromise methodology to determine the socio-optimal and sustainable policies for hydro-environmental management of groundwater resources, which simultaneously considers the conflicts and negotiation of involved stakeholders, uncertainties in decision makers' preferences, existing uncertainties in the groundwater parameters and groundwater quality and quantity issues. The fuzzy multi-objective simulation-optimization model is developed based on qualitative and quantitative groundwater simulation model (MODFLOW and MT3D), multi-objective optimization model (NSGA-II), Monte Carlo analysis and Fuzzy Transformation Method (FTM). Best compromise solutions (best management policies) on trade-off curves are determined using four different Fuzzy Social Choice (FSC) methods. Finally, a unanimity fallback bargaining method is utilized to suggest the most preferred FSC method. Kavar-Maharloo aquifer system in Fars, Iran, as a typical multi-stakeholder multi-objective real-world problem is considered to verify the proposed methodology. Results showed an effective performance of the framework for determining the most sustainable allocation policy in groundwater resource management.

Developing water quality management policies for the Chitgar urban lake: application of fuzzy social choice and evidential reasoning methods

Chitgar Lake is an artificial urban lake located in northwestern of Tehran, the capital city of Iran. It is estimated that the lake becomes highly eutrophic in the near future. In this paper, a methodology is presented for evaluating different water supply and water quality management policies proposed for this lake by utilizing evidential reasoning (ER) and fuzzy social choice (FSC) methods. The ER method can handle different kinds of uncertainties, such as fuzziness and ignorance, involved in analyzing lake water management alternatives. Since the ER method, as a multi-criteria single decision making technique, does not directly consider utilities of multiple stakeholders involved in the system, we also utilize a FSC method to reevaluate various lake water management alternatives. A set of 15 alternatives, rather than existing pattern of water supply for the lake, are proposed for the lake water quantity and quality management. Six assessment criteria are also considered for crisp or fuzzy evaluating the lake management alternatives. To evaluate the alternatives, the results of simulating the lake watershed using the storm water management model (SWMM) and model for urban stormwater improvement conceptualization (MUSIC) have been used. The application of the proposed methodology to the Chitgar Lake problem shows that using multi-criteria single decision making and multi-criteria multi-decision making methods can lead to different rankings for the same set of alternatives. Based on our evaluation, results of the FSC method, which directly incorporates the utility functions of stakeholders, look more promising.

Generalized manipulability of fuzzy social choice functions

In many social decision making contexts, a manipulator attempts to change the social choice in his favor by misrepresenting his preferences. This paper deals with the strategic manipulation problem of social choice functions aggregating fuzzy individual preferences. It defines how the strategic misrepresentation of fuzzy preferences can be profitable for an individual with a fuzzy weak preference relation. The case of max-$\top$-transitive fuzzy preference relations is considered where $\top$ is a t-norm. Then, the impossibility of building a non-manipulable fuzzy social choice function except the dictatorial one is established, generalizing thus the well-known Gibbard-Satterthwaite's result. The obtained results generalizes also the one of Ben Abdelaziz et al. for max-min transitive fuzzy preference relations.

On the manipulability of the fuzzy social choice functions

In many social decision-making contexts, a manipulator has incentives to change the social choice in his favor by strategically misrepresenting his preference. Gibbard [Manipulation of voting schemes: a general result, Econometrica 41(4) (1973) 587–601] and Satterthwaite [Strategy-proofness and Arrow's conditions: existence and correspondence theorems for voting procedures and social welfare functions. J. Econom. Theory 10 (1975) 187–217] have shown that any non-dictatorial voting choice procedure is vulnerable to strategic manipulation. This paper extends their result to the case of fuzzy weak preference relations. For this purpose, the best alternative set is defined in three ways and consequently three generalizations of the Gibbard–Satterthwaite theorem to the fuzzy context are provided.

Fuzzy social choice: a selective retrospect

One of the founders of social choice theory, Marquis de Condorcet, assigned truth degrees to propositions expressing preferences over options. Although his work is often discussed in terms of probability theory, it is arguable that his truth degree lends itself to a more natural interpretation as a fuzzy preference. We shall review some of Condorcet’s results in the light of this interpretation. The first twentieth century applications of fuzzy concepts to social choice appeared rather shortly after the introduction by L. A. Zadeh of the concept of fuzzy binary relation in early 1970s. The early applications dealt with experimental anomalies and their accountability with the aid of fuzzy preference relations and fuzzy goal states. Considerable literature now exists on various solution concepts in fuzzy voting games and many important theorems of traditional social choice theory have found their counterpart in fuzzy social choice. The natural next step would seem to be the design of fuzzy mechanisms and institutions.