A prospect theory-based group decision approach considering consensus for portfolio selection with hesitant fuzzy information

A multi-attribute decision-making method for the location selection of emergency rescue centers based on improved cumulative prospect theory under the background of ecological sustainable development

The location decision of the emergency rescue center, as a necessary link in the early stage to ensure the smooth development of emergency management, has become increasingly important. This paper analyzes the research theories and methods of location problem at home and abroad. By considering the decision-making psychological behavior of decision-makers, based on the idea of cumulative prospect theory, combined with the Pythagorean fuzzy multi-attribute evaluation method, this paper proposes a Pythagorean fuzzy multi-attribute decision-making evaluation method based on improved cumulative prospect theory. This method is to sort the results of each decision-making scheme by calculating the comprehensive cumulative prospect value. Based on the utility curve improved cumulative prospect theory, the research first depicts the psychological behavior characteristics of various decision-making groups under different risk preferences, and then designs a distance measurement method based on the geometric center of Pythagorean fuzzy right triangle. The main core of the distance measurement method is to convert Pythagorean fuzzy numbers into Pythagorean fuzzy right triangles. In the aspect of attribute weight assignment, a subjective and objective weighting method based on the combination of value function and deviation method of improved cumulative prospect theory is proposed. Finally, the Pythagorean fuzzy multi-attribute decision-making method based on the improved cumulative prospect theory is realized through the selection of reference objects, the calculation of value function value, weight function value and cumulative prospect value. This study takes the site selection of emergency rescue center in the construction period of Ya’an Linzhi Section of Sichuan Tibet Railway in China as an example, and proposes 10 emergency rescue centers as alternatives. Considering the different preferences of decision-makers, the improved decision-making method proposed in this paper is used to obtain the most optimal site selection scheme under different decision-making preferences.

Operational efficiency evaluation of urban and rural residents' basic pension insurance system by utilizing a picture fuzzy TOPSIS method based on the cumulative prospect theory

Population aging is the most serious challenge facing the pension insurance system in China in the next few decades. Compared with the employees of civil servants and enterprises and institutions, urban and rural residents are unstable vulnerable groups with less income. In order to deal with the pension risks caused by the growing aging population and solve the security problems of urban and rural residents, our government has carried out a series of constructive works in the pension insurance system: in view of the rural and urban residents, new rural social endowment insurance system and the social endowment insurance system for urban residents have been set up and combined into a unified basic old-age insurance system for urban and rural residents in 2014. With the continuous expansion in the scale of income and expenditure of urban and rural living insurance funds and the size of the insured number, it is of great necessity to evaluate the efficiency of this system. The operational efficiency evaluation of urban and rural residents' basic pension insurance systems is viewed as multi-attribute group decision-making (MAGDM). In this paper, we propose an approach by combining the traditional Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) with cumulative prospect theory (CPT) which can be widely used with vague information. Thus, the main contribution of this study is as follows: (1) the TOPSIS method is extended by picture fuzzy sets (PFSs) with unknown weight information; (2) entropy method to obtain the original weights of attributes; (3) the picture fuzzy-CPT-TOPSIS (PF-CPT-TOPSIS) method is used to deal with the MAGDM problems under PFSs; (4) a numerical instance for operational efficiency evaluation of urban and rural residents' basic pension insurance systems is proposed to testify the effectiveness of new method; and (5) some comparative studies are provided to give effect to the rationality of PF-CPT-TOPSIS approach.

Solution of Extended Multi-Objective Portfolio Selection Problem in Uncertain Environment Using Weighted Tchebycheff Method

In this paper, a mathematical model for an extended multi-objective portfolio selection (EMOPS) problem is explored with liquidity considered as another objective function besides the risk and return. The model is mathematically formulated in an uncertain environment. The concerned uncertainty is dealt with by employing the fuzzy numbers in the risk matrix and return. While the fuzzy EMOPS model is converted into the corresponding deterministic case based on the α—level sets of the fuzzy numbers, a weighted Tchebycheff method is implemented by defining relative weights and ideal targets. The merit of the suggested method is the applicability in many real-world situations. At the end, some numerical illustration is exhibited for the utility of the suggested EMOPS problem. Finally, it is concluded that the suggested method is simple to learn and to implement in real-life situations for the decision maker.

A multi-attribute decision-making method for the location selection of emergency rescue centers based on improved cumulative prospect theory under the background of ecological sustainable development

This research proposes a Pythagorean fuzzy multi-attribute decision-making evaluation method based on the improved cumulative prospect theory. The method ranks the decision-making results by calculating the comprehensive cumulative prospect value. Firstly, the research improves the cumulative prospect theory based on the utility curve, and describes the psychological and behavioral characteristics of various decision-making groups with different risk preferences. Then, a distance measure method based on the geometric center of the Pythagorean fuzzy right triangle is designed. The main core of the distance measure method is that it converts the Pythagorean fuzzy number into a Pythagorean fuzzy right triangle. In terms of attribute weighting, this research proposes a subjective and objective weighting method based on the combination of value function and deviation method of improved cumulative prospect theory. Finally, the Pythagorean fuzzy multi-attribute decision-making method based on the improved cumulative prospect theory is realized through the selection of reference object, the calculation of value function value, weight function value and cumulative prospect value. The results analysis and the comparison with other methods verify the effectiveness and advancement of the proposed decision-making method, especially that the proposed method has good applicability for the decision-making cases where the attribute value is Pythagorean fuzzy number, the attribute weight is unknown, and the psychological behavior of decision makers cannot be reflected.

Probabilistic Linguistic Matrix Game Based on Fuzzy Envelope and Prospect Theory with Its Application

Game theory is a powerful tool in modeling strategic interaction among rational players. However, as practical problems become more complex, uncertainty inevitably appears in the game. Due to the advantages of probabilistic linguistic term sets (PLTSs) in comprehensively and flexibly portraying uncertainty, fuzziness and hesitancy, this paper uses PLTSs to express players’ payoff values, and aims to develop an integrated method based on fuzzy envelope and prospect theory (PT) under a probabilistic linguistic environment for solving matrix games. In this method, an improved probabilistic ordered weighted averaging (POWA) operator is defined. Then, a novel trapezoidal fuzzy envelope for PLTSs is proposed and some related theorems are analyzed. Next, based on the defined cosine distance measure for PLTSs, the players’ psychological behavior in the game is considered by establishing the prospect value function. Besides, the applicability and practicability of the proposed method is verified with an example from the development strategy of Sanjiangyuan National Nature Reserve (SNNR) in China. Finally, some comparative analyses are carried out to illustrate the superiority of the proposed method. In order to improve the application of this proposed method, a decision support system (DSS) based on it is designed.

A large-scale group decision making method to select the ideal mobile health application for the hospital

Mobile health, which is not limited by time and space, can effectively alleviate the imbalance of medical resources. Currently, more and more hospitals begin to pay attention to online medical care and actively expand their mobile channels. Among of which, the cooperation with the third-party platform is an effective way to expand the online services of most hospitals. With the increasing number of mobile health applications (mHealth apps), it is difficult to select the ideal application. Most of the existing studies on mHealth app selection are conducted from the perspective of users who have health needs, which is insufficient. The views of multiple stakeholders should be taken into account. mHealth app selection can be regarded as a large-scale group decision making (LSGDM) problem. In this paper, a hybrid LSGDM method is proposed to select the mHealth app with the highest user satisfaction. First, the weights of criteria are obtained based on quality function deployment and 2-additive measure. Furthermore, a consensus model that considers cooperative and non-cooperative behaviors of decision makers is applied to select the ideal mHealth app. Finally, an illustrative example is implemented to exhibit the utility and validity of the proposed model.

Dynamic Reference Point-Oriented Consensus Mechanism in Linguistic Distribution Group Decision Making Restricted by Quantum Integration of Information

We present a consensus improvement mechanism based on prospect theory and quantum probability theory (QPT) that enables the manifestation of irrational and uncertain behaviors of decision makers (DMs) in linguistic distribution group decision making. In this framework, the DMs pursue the possibility of working with different partial agreements on prospect values. Considering that the reference information should be comprehensive and accurate as it guides information modification and affects consensus efficiency, objective and subjective information is integrated to obtain the information. Several studies have verified that the interference effect will occur when the brain beliefs flow towards the different decision classification paths. To address this problem, QPT is introduced into the information integration and the optimized value of the interference term can be acquired by the designed multi-objective programming model based on the maximum individual utility. Finally, as the reference point changes during the preference adjustment process, a dynamic reference point-oriented consensus model is constructed to obtain the optimized modification. A case study is performed on the emergency plan for the selection of designated hospitals, and comparative analyses are performed to demonstrate the feasibility and advantages of the proposed model. Several important insights are offered to simulate the most likely possibility of consciousness flowing into different decision classifications for DMs and moderators.

Evaluate the locations for smart waste bins using BWM and WASPAS methods under a probabilistic linguistic environment

 The decreasing resources of the earth and the deterioration of the environment are offering new challenges for handling waste management practices. The establishment of the smart waste bins plays an important role in promoting the development of waste classification and treatment fundamentally. We developed the evaluation system for the location selection problem of smart waste bins. Considering the uncertainty in the location selection of smart waste bins, the probabilistic linguistic term sets (PLTSs) are selected to express the evaluation information. Because of the excellent performance in weight-determing, the best worst method (BWM) is chosen to get the weight of criteria. While the weighted aggregated sum product assessment (WASPAS) method could handle both the qualitative and quantitative information, which are considered to derive the final ranking of the alternatives. This paper proposed a new group multi-criteria decision making approach integrating the BWM and the WASPAS with probabilistic linguistic information. Finally, in the empirical example, a sensitivity analysis shows that the proposed method is stable, a comparison analysis with PL-TOPSIS, PL-VIKOR, and PL-TODIM reflects its effectiveness and rationality, and the managerial implication verifies its usefulness and practicability, which also give guide to the company, government and resident.

A novel stochastic group decision-making framework with dual hesitant fuzzy soft set for resilient supplier selection

Suppliers can be regarded as unavoidable sources of external risks in modern supply chains, which may cause disruption of supply chains. A resilient supplier usually has a high adaptive ability to reduce the vulnerability against disruptions and recover from disruption to keep continuity in operations. This paper develops an effective multi-attribute group decision-making (MAGDM) framework for resilient supplier selection. Because of the many uncertainties in resilient supplier selection, the dual hesitant fuzzy soft sets (DHFSSs), a very flexible tool to express uncertain and complex information of decision-makers, is utilized to cope with it. In order to obtain the resilient supplier’s partial order relationship and consider the psychological behavior of decision-makers, this paper proposes the MAGDM framework with DHFSSs based on the TOPSIS method and prospect theory for resilient supplier selection. Furthermore, we consider the consensus level among experts of different backgrounds and experiences and propose a consensus measure method based dual hesitant fuzzy soft numbers (DHFSNs) before selecting a resilient supplier. The expert weights are calculated by the group consensus level between the expert and the group opinions. Meanwhile, we define the entropy of DHFSSs to determine the attribute weights objectively in the decision-making process. Based on this, the proposed method is applied to a practical manufacturing enterprise with an international supply chain for a resilient supplier selection problem. Finally, by performing a sensitivity analysis and a comparative analysis, the results demonstrate the robustness and validity of the proposed method.

Developing the modified R-numbers for risk-based fuzzy information fusion and its application to failure modes, effects, and system resilience analysis (FMESRA)

In order to identify and eliminate known or potential failures from the process of product design, development and production, failure mode and effect analysis (FMEA) have been widely used in a variety of industries as a useful tool in prognostics and health management, safety and reliability analysis. The traditional FMEA shows two significant flaws while calculating the risk priority number (RPN). First, recovery time that considerably affects the safety, cost, and sustainability of the system is not considered in the RPN calculation. Second, in order to capture different conflicting experts' views, especially when the obtained data are fuzzy, there is no mechanism. In order to overcome these issues, this paper presents a resilience-based risk priority number for considering the recovery and repair time of each failure mode, then a risk-based fuzzy information processing and decision-making is developed by modifying the R-numbers methodology and on the basis of simultaneous evaluation of criteria and alternatives (SECA) approach which is so-called R-SECA method. The capability of proposed models is tested by a case study of a centrifugal air compressor in a steel manufacturing company. Results show the robustness of proposed R-SECA model in dealing with different scenarios of risky information.

An extended TODIM approach for group emergency decision making based on bidirectional projection with hesitant triangular fuzzy sets

With the recent Covid-19 outbreak, group emergency decision-making (GEDM), as a new management model to pursue both social stability and decrease the negative impact of emergencies, has become highly popular. Evaluating and choosing the best emergency response is the core of the GEDM and selecting the choices can be regarded as a multi-attribute group decision-making (MAGDM) problem. Due to the increasing complexity and fuzziness of emergency decision-making environment, decision-makers (DMs) often cannot express completely rational preference information in many real EDM situations. At the same time, the existing methods seldom consider the DM's psychological mindset at the point of decision making. In this paper, an extended TODIM (an acronym for interactive and multi-criteria decision-making in Portugese) method based on bidirectional projection is proposed to solve the GEDM problem in the context of hesitant triangular fuzzy sets (HTFSs) and the novel method is applied to a case study and compared with other existing methods. The validity and applicability of the proposed method are discussed.

GRA method for waste incineration plants location problem with probabilistic linguistic multiple attribute group decision making

In this paper, we provide the probabilistic linguistic multiple attribute group decision making (PL-MAGDM) with incomplete weight information. In such method, the linguistic information firstly is shifted into probabilistic linguistic information. For obtaining the weight information of the attribute, two optimization models are built on the basis of the basic idea of grey relational analysis (GRA), by which the attribute weights can be obtained. Then, the optimal alternative is obtained through calculating largest relative relational degree from the probabilistic linguistic positive ideal solution (PLPIS) which considers both the largest grey relational coefficient (GRC) from the PLPIS and the smallest GRC form probabilistic linguistic negative ideal solution (PLNIS). Finally, a case study for waste incineration plants location problem is given to demonstrate the advantages of the developed methods.

Entropy-Based GLDS Method for Social Capital Selection of a PPP Project with q-Rung Orthopair Fuzzy Information

The social capital selection of a public–private-partnership (PPP) project could be regarded as a classical multiple attribute group decision-making (MAGDM) issue. In this paper, based on the traditional gained and lost dominance score (GLDS) method, the q-rung orthopair fuzzy entropy-based GLDS method was used to solve MAGDM problems. First, some basic theories related to the q-rung orthopair fuzzy sets (q-ROFSs) are briefly reviewed. Then, to fuse the q-rung orthopair fuzzy information effectively, the q-rung orthopair fuzzy Hamacher weighting average (q-ROFHWA) operator and q-rung orthopair fuzzy Hamacher weighting geometric (q-ROFHWG) operator based on the Hamacher operation laws are proposed. Moreover, to determine the attribute weights, the q-rung orthopair fuzzy entropy (q-ROFE) is proposed and some significant merits of it are discussed. Next, based on the q-ROFHWA operator, q-ROFE, and the traditional GLDS method, a MAGDM model with q-rung orthopair fuzzy information is built. In the end, a numerical example for social capital selection of PPP projects is provided to testify the proposed method and deliver a comparative analysis.