Comprehensive Prospect Value Research Articles

An integrated method for shared power bank supplier selection based on linguistic hesitant fuzzy multi-criteria group decision making

With the increasing number of smartphone users, the potential of the shared power bank industry is increasing. The shared power bank supplier selection can be regarded as a multi-criteria group decision making (MCGDM) problem with linguistic hesitant fuzzy (LHF) sets (LHFSs). This paper proposes a linguistic hesitant fuzzy MCGDM method based on the MULITMOORA (Multi-Objective Optimization on basis of a Ratio Analysis plus the Full Multiplicative form), the BWM (best and worst method), and the prospect theory (PT). Firstly, a new comparison approach of LHFSs is proposed. We propose the LHF Bonferroni mean (BM), the LHF weighted BM and the LHF generalized weighted BM (LHFGWBM) operators. The decision makers’ weights are acquired via a tri-objective optimization model. This paper extends the BWM to obtain the subjective criteria weights and employs the entropy to acquire the objective criteria weights. The comprehensive criteria weights are generated by the Jenson-Shannon divergence. The LHFGWBM operator is used to generate the collective decision matrix. The comprehensive prospect value decision matrix is obtained. Then, we propose the PT-based MULTIMOORA method for LHF MCGDM. An example of shared power bank supplier selection is used to show the superiorities of the proposed LHF MCGDM method.

An Emergency Decision-Making Method for Coal Spontaneous Combustion Based on Improved Prospect Theory

In response to the limited available information during the initial stages of coal spontaneous combustion and the influence of decision makers’ risk preferences on decision-making, this paper proposes an emergency decision-making method for coal spontaneous combustion that integrates grey correlation degree and TOPSIS with an enhanced prospect theory. Firstly, a normalized weighted evaluation matrix is established for the emergency response plan of coal spontaneous combustion, and the entropy method is utilized to determine the weights of various indexes. Then, considering the imperfect rationality of decision makers and their diverse individual risk preferences, they are categorized into three types: risk-seeking type, risk-neutral type, and risk-averse type. The corresponding risk coefficients are determined based on these different types. Positive and negative ideal solutions are taken as reference points, and matrices representing gains and losses are constructed. The grey correlation degree is introduced to calculate both positive and negative prospect values based on these matrices. Moreover, the prospect value for each emergency response plan is calculated, respectively, based on different types of decision makers, and the entropy method is used to assign weights to decision makers according to their respective risk preferences. Consequently, based on these prospect values and the weights, comprehensive prospect values for each emergency response plan are obtained and ranked to identify the optimal one. Finally, in order to validate the effectiveness of our proposed approach, a case study is conducted, and the results obtained from this case study are discussed and compared with those from other methods.

A three-parameter interval number group decision-making method based on kernel and greyness degree

A decision method based on kernel and greyness degree is proposed for group decision-making problems in which attribute values are represented by three-parameter interval grey numbers, whose kernel and greyness degree are modified. The prospect value of each program’s evaluation information given by decision-makers is solved by using prospect theory. Finally, the reasonable decision-makers weight should make the total weighted prospect value of the scheme the maximum, the deviation between the evaluation information of each decision-maker, the mean value of the evaluation information the minimum, and the greyness degree deviation value of the information which is given by decision makers the minimum. The weight vector of the decision-makers is obtained by solving this model, and the comprehensive prospect value of the solution is used to rank the alternatives. Finally, taking a commercial aircraft parts supplier selection as an example, the rationality of the method is verified.

The Probabilistic Dual Hesitant Fuzzy Multi-Attribute Decision-Making Method Based on Cumulative Prospect Theory and Its Application

Addressing the complex issue of multi-attribute decision-making within a probabilistic dual hesitant fuzzy context, where attribute weights are unknown, a novel decision-making method based on cumulative prospect theory is proposed, named the probabilistic dual hesitant fuzzy multi-attribute decision-making method based on cumulative prospect theory. Firstly, a decision matrix is formulated, representing probabilistic dual hesitant fuzzy information. Secondly, according to the decision maker’s authentic preference and non-membership information sensitivity, a comprehensive score function suitable for probabilistic dual hesitant fuzzy elements is proposed. The attribute weights are then determined using the entropy method. Next, the value function and decision weight function from the cumulative prospect theory are employed to compute the cumulative prospect value attributed to each available scheme. In addition, a cumulative prospect matrix is constructed, enabling the establishment of scheme rankings based on the comprehensive cumulative prospect value. Finally, the analysis of specific cases and a comparative assessment of methods pertaining to the selection of emergency response schemes collectively demonstrate the rationality and efficacy of the decision-making method presented in this study.

A Two-Stage Bilateral Matching Study of Teams-Technology Talents in New R&D Institutions Based on Prospect Theory

This study considers two-stage bilateral matching of teams and scientific and technological talents in new R&D organizations and proposes a two-stage dual-objective bilateral matching method based on prospect theory. The matching of teams and scientific and technological talent in new R&D institutions is divided into two stages: elimination matching in the first stage and selection matching in the second stage. In the first stage, the evaluation index of the team to talent and the cost index of talent are constructed, the dual reference points of peer and expectation are set for evaluating talent, and the bottom-line reference points are set for talent cost. The comprehensive prospect value in the first stage is calculated based on prospect theory, and the matching in the first stage is completed based on the dual-objective optimization model with the highest evaluation value and the lowest cost value. In the second stage, using the matching results of the first stage, the team evaluates the talent again, while the talent ranks the team to obtain the satisfaction value, and completes the second stage of bilateral matching based on prospect theory and the dual-objective optimization model with the highest evaluation value and the highest satisfaction value. Finally, a case study and method comparison show that the proposed method is feasible and effective.

Integrated Energy System Evaluation Method Based on Minimum Cross-Entropy and Prospect Theory

An integrated energy system can improve the reliability and flexibility of the energy supply, and has good economic and environmental benefits. Integrated energy system evaluation is of great significance to the implementation of an integrated energy system project. The integrated energy system evaluation method is presented based on the minimum cross-entropy model and the prospect theory. Firstly, the minimum cross-entropy model is used to obtain the comprehensive column vector of each evaluation index. Secondly, the index weight is determined according to the different weight methods. Finally, through the establishment of positive and negative prospect value matrices, according to the comprehensive prospect value, the advantages and disadvantages of integrated energy system schemes are sorted. The effectiveness of the proposed method is verified by hotel-integrated energy system data.

A Multi-stage Scheme Decision Model for Complex Products Based on Prospect Theory and Earned Value Method

The development process of complex products is highly uncertain and risky, cause the balance among progress, cost and technology needs to be comprehensively considered. Therefore, how to make decisions on key development plans becomes a problem that needs to be studied and solved. The existing multistage decision model needs to determine the complete stage division, quantity and attribute value of all alternatives in each stage of the development process at the beginning of the decision. However, actually, given the characteristics of long cycle of complex products, high technical risks, and many uncertainties, it is difficult to give the above information in advance in practical work. Therefore, in view of the above shortcomings, this paper proposes a multi-stage scheme decision-making method based on prospect theory and earned value method. First, based on the current progress and cost performance of the project, the dynamic reference point is set by analyzing the deviation between the actual implementation and the plan; Then, the dynamic prospect values of the schedule, cost and technical indicators of each alternative are calculated, and the optimal attribute weights and the comprehensive prospect values of each alternative are obtained by constructing a linear programming model; Finally, the advantages and innovation of the proposed model are further demonstrated through specific application examples.

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.

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.

Decision optimization of emergency material support based on blockchain under major public health emergencies

The work intends to relieve the pressure on the urban medical system and reduce the cross-infection of personnel in major public health emergencies. On the premise of an in-depth analysis of the utility risk entropy algorithm model and prospect theory, the decision-making of major health emergencies is proposed. Firstly, the utility risk entropy algorithm model is optimized, and the main decision-making members are subjected to utility perception according to the perceived utility values of different levels of risk, and the weights of decision-making members are calculated and revised according to the results of utility clustering. Secondly, the prospect theory is optimized. Taking the zero as the reference point to calculate the prospect value, and taking the maximization of the comprehensive prospect value as the objective to optimize the model, the comprehensive prospect value of each scheme is calculated and sorted. Finally, the proposed scheme is tested, and the test results show that in the optimal decision-making time of the scheme, the optimal decision-making time is 0 every day. When the epidemic situation is in the first cycle, the decision-making loss of the optimal scheme is 2.69, and the reduction ratio of the optimal scheme decision-making loss is 63.96%. When the epidemic situation is in the second cycle, the decision-making loss of the optimal scheme is 0.65, and the reduction ratio of the optimal scheme decision-making loss is 94.44%. When the epidemic situation is in the third cycle, the decision-making loss of the optimal scheme is 0.22, and the reduction ratio of the decision-making loss of the optimal scheme is 89.39%. The proposed scheme can improve the processing efficiency of major health emergencies and reduce the risk of accidents.

Grey Multiattribute Emergency Decision-Making Method for Public Health Emergencies Based on Cumulative Prospect Theory

In view of the different risk preferences of decision-makers and the information gap in the timing of the subjects under evaluation, a multiattribute dynamic decision-making model that considers decision risk in addition to the priority of time is proposed. First, to account for the uncertainty of the evaluation information, the interval grey number method was applied to perform numerical abstraction and key data feature extraction on the scene of public health emergencies and to obtain the information after attributes were unified. Second, acknowledging the bounded rational behavior of actual decision-makers, the decision-makers’ risk preference was introduced into emergency decision-making. In combination with the time degree, the multiattribute unified decision matrix was transformed into an expected dynamic cumulative prospect decision matrix. Furthermore, based on cumulative prospect theory (CPT), the prospect value function and the weight function are constructed; a new optimization model is proposed to obtain the attribute weight. And according to the comprehensive prospect value of each alternative, the priority of the alternatives was determined. Finally, with the COVID-19 epidemic serving as an example, the results confirm that the emergency decision-making method proposed in this paper is feasible and effective.

Prospect Theory-Based optimal configuration of modular mobile battery energy storage in distribution network considering disaster scenarios

The comprehensive utilization of energy storage and the resilience of power grid in disaster scenarios are critical research objects in distribution network. However, the traditional literatures were mainly focused on the fixed energy storage devices. Meanwhile, conventional energy storage planning did not consider its utility in disaster scenarios. In this paper, a prospect theory-based optimal configuration of modular mobile battery energy storage (MMBES) is proposed to tackle the shortcomings. To better leverage the capabilities of MMBES, operation and coordination under normal, fault and disaster scenarios are studied, and five attributes of the energy storage configuration are extracted by analyzing various beneficial types. Then, a prospect theory-based optimal configuration model is established to maximize the comprehensive prospect value with the consideration of uncertain disaster scenarios. Sub-models of network loss reduction, reliability improvement, delay of network expansion, outage cost in disaster scenarios, and installation cost are well integrated. Finally, the established non-linear optimization model is solved by utilizing the differential evolution approach. Case studies demonstrate that the flexible application of MMBES can significantly improve the comprehensive benefits and that the optimal configuration can reflect the preference of decision makers.

Understanding Electric Bicycle Users’ Mode Choice Preference under Uncertainty: A Case Study of Shanghai

The electric bicycle is considered as an environmentally friendly mode, the market share of which is growing fast worldwide. Even in metropolitan areas which have a well-developed public transportation system, the usage of electric bicycles continues to grow. Compared with bicycles, the power transferred from the battery enables users to ride faster and have long-distance trips. However, research on electric bicycle travel behavior is inadequate. This paper proposes a cumulative prospect theory (CPT) framework to describe electric bicycle users’ mode choice behavior. Different from the long-standing use of utility theory, CPT considers travelers’ inconsistent risk attitudes. Six socioeconomic characteristics are chosen to discriminate conservative and adventurous electric bicycle users. Then, a CPT model is established which includes two parts: travel time and travel cost. We calculate the comprehensive cumulative prospect value (CPV) for four transportation modes (electric bicycle, bus, subway and private car) to predict electric bicycle users’ mode choice preference under different travel distance ranges. The model is further validated via survey data.

Emergency plan selection for epidemic prevention and control based on cumulative prospect theory and hybrid-information MADM

PurposeDecision-making problems in emergency plan selection for epidemic prevention and control (EPAC) are generally characterized by risky and uncertainty due to multiple possible emergency states and vagueness of decision information. In the process of emergency plan selection for EPAC, it is necessary to consider several obvious features, i.e. different states of epidemics, dynamic evolvement process of epidemics and decision-makers' (DMs') psychological factors such as risk preference and loss aversion.Design/methodology/approachIn this paper, a novel decision-making method based on cumulative prospect theory (CPT) is proposed to solve emergency plan selection of an epidemic problem, which is generally regarded as hybrid-information multi-attribute decision-making (HI-MADM) problems in major epidemics. Initially, considering the psychological factors of DMs, the expectations of DMs are chosen as reference points to normalize the expectation vectors and decision information with three different formats. Subsequently, the matrix of gains and losses is established according to the reference points. Furthermore, the prospect value of each alternative is obtained and the comprehensive prospect values of alternatives under different states are calculated. Accordingly, the ranking of alternatives can be obtained.FindingsThe validity and robustness of the proposed method are demonstrated by a case calculation of emergency plan selection. Meanwhile, sensitivity analysis and comparison analysis with fuzzy similarity to ideal solution (FTOPSIS) method and TODIM (an acronym in Portuguese for interactive and MADM) method illustrate the effectiveness and superiority of the proposed method.Originality/valueAn emergency plan selection method is proposed for EPAC based on CPT, taking into account the psychological factors of DMs.HighlightsThis paper proposes a new CPT-based EDM method for EPAC under a major epidemic considering the psychological factorsof DMs, such as risk preference, loss aversion and so on.The authors' work gives approaches of normalization, comparison and distance measurement for dealing with the integration of three hybrid formats of attributes.This article gives some guidance, which contributes to solve the problems of risk-based hybrid multi-attribute EDM.The authors illustrate the advantages of the proposed method by a sensitivity analysis and comparison analysis with existing FTOPSIS method and TODIM method.

An improved three-way decision model based on prospect theory

In three-way decision, how to describe the risk attitudes of decision-makers is an important issue. The prospect theory is widely used to reflect decision-makers' risk attitudes and the decision rules are based on the maximum prospect value. However, the previous three-way decision models based on prospect theory neglected time outcome or they included time outcome in monetary outcome in decision process. In fact, in some cases, time outcome is a more important element in decision making, and without considering it directly may weaken the rationality of decision results. To address these problems, we construct an improved three-way decision model based on prospect theory, which simultaneously and directly considers time outcome and monetary outcome. Specially, this model is a multi-objective optimization model. Firstly, prospect theory is used to describe decision-makers' risk attitudes toward monetary gains and losses as well as time gains and losses. Secondly, we construct a multi-objective optimization model and introduce preference coefficients to transform it into a single objective optimization model, which is based on the maximum comprehensive prospect value. Further, the existence and uniqueness of thresholds are proven, and the decision rules are given. Finally, an illustrative example and some comparative analyses are presented, which validate the rationality and superiority of our improved model.

Behavioral Risky Multiple Attribute Decision Making with Interval Type-2 Fuzzy Ranking Method and TOPSIS Method

Considering the decision maker’s psychological state will influence their evaluation result in the risky multi-attribute decision-making problem, and the uncertainty of evaluation information. In this paper, we will propose a behavioral risky multiple attribute decision making with interval type-2 fuzzy ranking method and TOPSIS method. The interval type-2 fuzzy set is used to express the uncertainty of evaluation information, the prospect theory is applied to describe people’s psychological state in the processing of risk decision making. First, we define a new ranking method for interval type-2 fuzzy set to compare the interval type-2 fuzzy evaluation information and the expectation. Second, we give a relative distance for interval type-2 fuzzy set to get the distance between the interval type-2 fuzzy evaluation information and expectation. Third, we use the prospect theory, the new defined ranking method and the new defined distance formula to obtain the comprehensive prospect value. Fourth, we use the improved TOPSIS method and the comprehensive prospect value to rank the alternatives. Based on the above-mentioned steps, we give the solution for risky interval type-2 fuzzy multiple attribute decision-making problem, which named as the behavioral risky multiple attribute decision making with interval type-2 fuzzy ranking method and TOPSIS method. Finally, we use an example to show the rationality of this method.

A Public-Participation-Based Mixed Multiattribute Decision-Making Approach for Major Public Affairs

The decision-making activities of major public affairs are closely related to the public, so the decision results of such affairs must be supported by the public. The public must participate in decision-making activities to ensure their effectiveness, which further increases the complexity. In addition, attribute information and public opinion usually present different forms of expression in this type of problem, making decision-making more difficult. Therefore, a suitable decision approach must be chosen to deal with this type of decision problem. This paper addresses the decision-making characteristics of major public affairs and proposes a public-participation-based decision-making approach for mixed multiattribute decision-making problems in major public affairs. The proposed approach can work with entirely unknown attribute weights and decision-making values represented in multiple formats. First, the statistical distribution of public opinions is determined based on the expectation of the attributes, resulting in decision-making reference points for various attributes. The different forms of attributes and reference points are unified. Then, the values of the attributes and reference points are standardized. Afterward, the attribute prospect value for each alternative is calculated using the attribute value and corresponding reference points. The attribute weight intervals are determined based on the importance information of the attributes provided by the public. An optimization model is established to determine the attribute weights to maximize the alternative attribute deviation. Next, the comprehensive prospect value of each alternative is obtained to determine the ranking of the alternatives. Finally, a case analysis is conducted with a method comparison and sensitivity analysis, and the feasibility and effectiveness of the proposed approach are verified. In the proposed method, the reference points for each attribute are set according to the distribution characteristics and ambiguity of public expectations, guaranteeing that public expectations can be effectively reflected in the attribute reference points. In the process of attribute weighting, based on the information for the attribute importance given by the public, the range of attribute weights is determined. Then, we obtain the exact value of the attribute weights using an optimization model to maximize the alternative attribute deviation. The final result of the attribute weights ensures the full expression of public opinion and can improve the differentiation of decision results, which is convenient for ranking alternatives. During evaluation of the alternatives based on prospect theory, the expression forms of attributes and reference points are unified. Subsequently, the values of them are normalized, which satisfy the decision-making requirement of major public affairs.

Decision-Making for Fire Emergency of Urban Rail Transit Based on Prospect Theory

Fire emergency response of urban rail transit is a complex multiattribute risk decision-making problem. In emergency response analysis, it is necessary to consider the psychological behaviors of decision-makers such as reference dependence, loss aversion, and judge distortion. Applying different emergency plans can intervene the development and evolution of urban rail emergency fire and may even result in different levels of casualties and property losses. For this situation, this paper proposes an emergency response decision-making method based on prospect theory. First, according to the prospect theory, this paper quantitatively describes the comprehensive psychological perception of decision-makers for casualties and property losses in different situations. Then, the psychological perception of decision-makers for the important levels of different situations is calculated. Third, according to the situation comprehensive values, situation weights, and the cost inputs of emergency plans, the comprehensive prospect values of each emergency plan are calculated, and the fire emergency plans can be ranked based on comprehensive prospect value. At last, the fire emergency disposal of Tianjin rail transportation line 3 is considered as the background in this paper. The feasibility and effectiveness of the purposed method is illustrated through the case study.

A dynamic grey target evaluation method with multiple reference points for new R&D institution performance

As a new business form of innovation and development, new R&D institutions are characterized by their focus on regional and industrial major technical needs, diversified investment subjects, diversified construction models, and marketization of operation mechanism. Their performance evaluation faces new problems and challenges. This paper proposes a new dynamic grey target evaluation model of R&D institutions’ performance in regard to four evaluation indexes, three reference points, and four stages. Aiming at resolving the multi-attribute dynamic decision problem with the attribute value being an interval grey number and the decision-maker’s weight information unknown, we propose the use of the close degree of grey incidence method to determine the index weight. Our approach revolves around three reference points: peers, development, and expectations. Value matrices of the three reference points are expressed according to the Cumulative Prospect Theory, which also determines the distance from the center of the grey target. Based on the Orness measure, we establish a multi-stage weight optimization model to calculate the stage weight and the comprehensive cumulative prospect value of each agency. Finally, we verify the validity and practicability of our method with the use of parameter sensitivity analysis, a comparison with other methods, and a case study.

Research on Traffic Assignment Model and Algorithm Based on Cumulative Prospect Theory under Uncertain Factors

Current traffic assignment theories and methods are studied. To address the limitations of existing models and algorithms in solving the traffic assignment problems under uncertain supply and demand, a traffic assignment model based on the cumulative prospect theory is proposed. Firstly, the problem of uncertain supply and demand of the traffic network is described, and an improved traffic impedance function of road sections is proposed. Then, the reference point of generalized cost and the reference point of the dynamic section risk are set up, and the comprehensive cumulative prospect value function considering the preference coefficient of the reference point is given. A traffic assignment model based on the cumulative prospect theory is constructed, and an isolation niche genetic simulated annealing algorithm is designed to solve the model. Finally, with the highway traffic network in the Sichuan-Tibet region as an example, the process of network traffic equilibrium based on the cumulative prospect theory under the fixed and changing network structure is studied respectively, and parameter sensitivity and algorithm comparison are analyzed. The results show that the proposed traffic assignment model based on the cumulative prospect theory provides a good idea for solving the traffic assignment problem under uncertain supply and demand, and is of theoretical significance and application value.