Risk decision-making method using interval numbers and its application based on the prospect value with multiple reference points

Zhu, Jianjun; Ma, Zhenzhen; Wang, Hehua; Chen, Ye

doi:10.1016/j.ins.2017.01.007

Cited by 45 publications

(31 citation statements)

References 51 publications

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“…Through setting the reference points, DMs can acquire better knowledge of the detailed status of alternatives. In general, positive ideal points are helpful for reflecting the gap between one alternative and other external competitors, and thus for illustrating the competitive advantages of the outward attributes [22]. Moreover, the key part of applying PT is to determine the positive or negative distance between alternatives and reference points.…”

Section: B Prospect Theory -Based Integration Of Evaluation and Pre-mentioning

confidence: 99%

“…Compared with other methods [2], [39], [40], an optimization model with the maximum deviation [36], aiming at sorting the alternatives by the weight of each attribute, is more effective for sorting alternatives with certain distinction degree. The greater contribution of one attribute on the summation of weighted values' deviations of the alternatives indicates the greater importance of the attribute, and thus a higher weight value is assigned, and vice versa [22]. For that reason, the attribute-weighting model in this study has been built by using the maximum deviation method.…”

Section: An Optimization Model For Incomplete Attribute Weightmentioning

confidence: 99%

“…In PT, the value function is assumed to be a S-shape curve, denoting the risk aversion of DMs in face of gains and the risk propensity in case of losses [17]. Thus, PT is more applicable in real-world applications [22], [23]. When applying PT in decision-makings, distance measure for normal cloud models is quite significant for disclosing the relevance between alternatives and reference points, and has been investigated in some studies, such as maximum-minimum-value based distance measurement [4], [7], [24], Hamming distance [25], arithmetic square rootbased distance measurement [14], relative entropy distance measurement [23] , cosine similarity measure [26], and fuzzy distance measure [27].…”

Section: Introductionmentioning

confidence: 99%

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Risk-Based Multi-Attribute Decision-Making for Normal Cloud Model Considering Pre-Evaluation Information

Zhang

2020

IEEE Access

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An uncertain multi-attribute decision-making (MADM) problem is studied based on cloud models. Cloud models, referring to fuzziness and randomness, are utilized to depict evaluation and preevaluation information which can reflect the future development performance of alternatives. Because of bounded rationality, decision maker's (DM) risk attitudes should be considered when facing uncertainty. Thus, a behavioral MADM (BMADM) method is proposed by considering DM's risk attitudes and preevaluation. First, a distance measure for normal cloud models is developed with consideration of both DM's risk preferences and random distribution, aiming at making full use of information. Second, as a basis of applying prospect theory, positive ideal reference point is set by considering both evaluation and preevaluation information from three aspects: risk-averse, risk-neutral, and risk-seeking preference coefficients, in which the sign of distance is not necessary to determine. The third element is the establishment of an optimization model for handling incomplete attribute weights, following which is to obtain the ranking of alternatives. The final phase is the application of the proposed method to one case, along with sensitivity and comparison analyses, as a means of illustrating the applicability and feasibility of the new method. INDEX TERMS multi-attribute decision making, normal cloud model, risk attitudes, pre-evaluation information, prospect theory.

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Section: B Prospect Theory -Based Integration Of Evaluation and Pre-mentioning

confidence: 99%

Section: An Optimization Model For Incomplete Attribute Weightmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Risk-Based Multi-Attribute Decision-Making for Normal Cloud Model Considering Pre-Evaluation Information

Zhang

2020

IEEE Access

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“…Li and Zhang [26] introduced a useful method to solve DMADM problems with three-parameter interval gray numbers on the basis of prospect theory. Zhu et al [27] considered multiple reference points in MADM problems with the interval numbers of attribute values. Dai et al [28] introduced a method that considered dynamic information to solve MADM problems with attribute values, which are triangular fuzzy numbers.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Hybrid Multiple Attribute Decision‐Making Problem Based on Reference Point Adaptation

Zhang

Sun

et al. 2019

Mathematical Problems in Engineering

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Individuals’ decision-making depends on reference points in prospect theory. This research considers the bounded rationality of decision makers and constructs a dynamic hybrid multiple attribute decision-making (DHMADM) model. Unlike existing models, the DHMADM model focuses on dynamic reference point, which has been proven in prospect theory. This research presents the effects of reference point adaptation on decision-making through model calculation. The optimal choice of decision makers changed with the change of the reference point in the DHMADM model. By experiment, we found that the DHMADM model considering reference point adaptation can more accurately express the final choice of decision makers than models only considering the static reference point.

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“…For example, Lu et al investigated risk-type decision-making problems concerning the DRPs of social and financial matters [26]. Zhu et al developed a risk decision-making method with two or three reference points [27]. Pei et al studied dynamic hybrid multi-attribute group decision-making problems with DRPs [28].…”

Section: Introductionmentioning

confidence: 99%

A Method of Multi-Attribute Decision Making With Double-Reference Points and its Application in Location of Agricultural Products Logistics Center

2019

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A single reference point (SRP) is typically employed in traditional studies on the multi-attribute decision making (MADM) method. However, SRP lacks the advantage of the multiplicity of reference points and is thus unable to adequately describe loss aversion actions. With the goal of determining the loss aversion characteristics of decision makers, this work proposes an MADM method that is based on double reference points (DRPs) to solve the MADM problem using crisp and interval fuzzy numbers. First, this work describes the universality of decision-making problems with DRPs and then evaluates the characteristics of DRPs and their effects on decision making. Second, attitude and utility functions are established on the basis of the requirements of loss aversion. Third, considering the ''one-vote veto'' characteristic of a ''dissatisfaction'' attitude, a binary utility value is created by integrating the occurrence probability p, and the utility value u. The fourth, the main characteristics of and the aggregation method for the binary utility value are analyzed and established. Finally, a new decision-making method is applied to resolve the location decision of an agricultural product logistics center. Results indicate that the relationship between attribute and reference point significantly influences decision behavior. Compared with the traditional decision-making method, the proposed decision-making method can effectively identify the feasibility levels of alternatives. The ranking of the proposed decision-making method for feasible alternatives is basically the same as that of the traditional decision-making method. These results can effectively help solve agricultural engineering problems and broaden the coverage of and provide references for MADM research. INDEX TERMS Double reference points (DRPs), loss aversion, multi-attribute decision-making (MADM), utility, agricultural product logistic center.

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Risk decision-making method using interval numbers and its application based on the prospect value with multiple reference points

Cited by 45 publications

References 51 publications

Risk-Based Multi-Attribute Decision-Making for Normal Cloud Model Considering Pre-Evaluation Information

Risk-Based Multi-Attribute Decision-Making for Normal Cloud Model Considering Pre-Evaluation Information

Dynamic Hybrid Multiple Attribute Decision‐Making Problem Based on Reference Point Adaptation

A Method of Multi-Attribute Decision Making With Double-Reference Points and its Application in Location of Agricultural Products Logistics Center

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