Travelers' Risk Attitude Classification Method Based on Cumulative Prospect Theory and Experimental Results

Author(s):  
Chao Yang ◽  
Binbin Liu ◽  
Lianyan Zhao ◽  
Xiangdong Xu
2009 ◽  
pp. 254-270
Author(s):  
Fei-Chen Hsu ◽  
Hsiao-Fan Wang

In this chapter, we used Cumulative Prospect Theory to propose an individual risk management process (IRM) including a risk analysis stage and a risk response stage. According to an individual’s preferential structure, an individual’s risk level for the confronted risk can be identified from risk analysis. And based on a response evaluation model, the appropriate response strategy is assessed at the risk response stage. The applicability of the proposed model is evaluated by an A-C court case. The results have shown that the proposed method is able to provide more useful and pertinent information than the traditional method of decision tree by using the expected monetary value (EMV).


2019 ◽  
Vol 2019 ◽  
pp. 1-11
Author(s):  
Chang-feng Zhu ◽  
Zheng-kun Zhang ◽  
Qing-rong Wang

We study the problem of path choice for emergency logistics in this paper. Based on the uncertainty environment during the path choice from emergency logistics network and the bounded rationality of decision makers, cumulative prospect theory is introduced to study the problem of emergency logistics path choice with comprehensive consideration of path properties and risk attitude of decision makers. In addition, the decision behavior of decision maker with the attitude of risk seeking and risk aversion under limited rationality is comprehensively analyzed respectively. Based on the choice behavior, a strategy to demarcate the value of reference point value is also proposed, and an optimization model is used to obtain the combined weight based on the moment estimation. Finally, both the theory and model are verified by calculation and compared analysis in a case study. In addition, perturbation analyses of related parameter are carried out to further reveal the influence mechanism between the prospect value of each path and related parameters. The result shows that the decision-making model can make emergency logistics path choice with higher efficiency and reliability under different complex interference conditions.


2019 ◽  
Vol 136 ◽  
pp. 04067 ◽  
Author(s):  
Yihua Wang ◽  
Mengke Yang ◽  
Xiaoguang Zhou

In recent years, sudden natural disasters occur frequently. Typical emergencies have the characteristics of great uncertainty, large-scale casualty risk, time pressure and urgency, which have a series of serious and sustained impacts on people's production and life. Therefore, after the emergencies, emergency rescue is particularly important for disaster-stricken areas, and the decision-making of emergency logistics is an important part of it. At present, the research on emergency logistics in China focuses on the shortest distribution time, multi-objective decision-making, dynamic path planning, and operational research. It is believed that people are completely rational in making decisions, ignoring people's subjective factors and risk attitudes. From the perspective of decision-makers' risk attitude, this paper studies people's decision-making bias under the condition of incomplete rationality. Based on previous studies, this paper determines the value coefficient and weight coefficient, and according to the characteristics of emergency logistics, time is selected as the reference point., and A path selection model based on cumulative prospect theory is established. According to the risk attitude, the decision maker is divided into risk preference type and risk avoidance type. Based on the established model, an example is simulated, and the parameters in the model are simulated, and the impact of risk attitude and parameter changes on the final decision-making is analyzed. The simulation results show that the cumulative prospect theory is applicable to the study of emergency logistics decision-making mechanism, and the parameter setting will also have an important impact on the path prospect.


2021 ◽  
pp. 1-18
Author(s):  
Tao Zhang ◽  
Shizheng Li ◽  
Jin Wang

China has proposed medical couplet body to alleviate residents’ difficulties in seeking medical treatment, and the future development ability of medical couplet body has gradually become a research interest. On the basis of prospect theory, this study constructs a comprehensive evaluation index system with qualitative and quantitative indexes, clear hierarchy, and diverse attribute characteristics. The development ability of medical couplet body is also comprehensively and systematically evaluated. In addition, the evidential reasoning method is proposed on the basis of the equivalent transformation of prospect value. Furthermore, the validity and feasibility of the model are proven through experiments, and the influence of decision makers’ risk attitude on the evaluation results is discussed.


2021 ◽  
pp. 1-13
Author(s):  
Ning Tao ◽  
Duan Xiaodong ◽  
An Lu ◽  
Gou Tao

A disruption management method based on cumulative prospect theory is proposed for the urgent with deteriorating effect arrival in flexible job shop scheduling problem (FJSP). First, the mathematical model of problem is established with minimizing the completion time of urgent order, minimizing the total process time of the system and minimizing the total cost as the target. Then, the cumulative prospect theory equation of the urgent arrival in job shop scheduling process is induced designed. Based on the selected model, an optimized multi-phase quantum particle swarm algorithm (MQPSO) is proposed for selecting processing route. Finally, using Solomon example simulation and company Z riveting shop example as the study object, the performance of the proposed method is analyzed. It is compared with the current common rescheduling methods, and the results verify that the method proposed in this paper not only meets the goal of the optimized objects, but improves the practical requirements for the stability of production and processing system during urgent arrival. Lastly, the optimized multiphase quantum particle swarm algorithm is used to solve disruption management of urgent arrival problem. Through instance analysis and comparison, the effectiveness and efficiency of urgent arrival disruption management method with deteriorating effect are verified.


Sign in / Sign up

Export Citation Format

Share Document