A Cumulative Prospect Theory Approach to Passengers Behavior Modeling: Waiting Time Paradox Revisited

2004 ◽  
Vol 8 (4) ◽  
pp. 195-204 ◽  
Author(s):  
EREL AVINERI
Keyword(s):  
Prospect Theory ◽  
Waiting Time ◽  
Cumulative Prospect Theory ◽  
Behavior Modeling ◽  
Theory Approach

scholarly journals A CUMULATIVE PROSPECT THEORY APPROACH TO CAR OWNER MODE CHOICE BEHAVIOUR PREDICTION

Transport ◽  
2014 ◽  
Vol 29 (4) ◽  
pp. 386-394 ◽  
Author(s):  
Shi An ◽  
Xiaowei Hu ◽  
Jian Wang
Keyword(s):  
Prospect Theory ◽  
Utility Theory ◽  
Mode Choice ◽  
Congestion Pricing ◽  
Cumulative Prospect Theory ◽  
Middle Level ◽  
Subjective Perception ◽  
Theory Approach ◽  
Choice Behaviour ◽  
Pricing Policy

The uncertain transportation environment makes travel’s mode choice decision-making behaviour become a complex and alterable process. Based on the cumulative prospect theory, this paper analysed the long-standing use of utility theory for the travel’s mode choice behaviour research. Car owner’s generalized cost includes the transport fare, travel time cost and penalty cost (early or delay); cumulative prospect theory was applied to describe the uncertain and risky prospect of car owner under congestion pricing policy. Through analysing two kinds of car owner’s generalized subjective perception costs on the four different transportation modes, including bus, subway, taxi and private car; we calculated the mode choice’s prospect value before and after the implementation of congestion pricing, and compared the difference of numerical example between cumulative prospect theory and expected utility theory. The results indicated that after the implementation of congestion pricing policy, the middle-level income car owner would prefer to choose taxi. Based on a state preference survey on travel’s mode choice behaviour, the survey results further validated our analysis. This paper for the first time adopted cumulative prospect theory to analyse travel’s mode choice behaviour after the implementation of congestion pricing policy, which can better explain car owner’s mode choice decisionmaking process under uncertain and risk condition. This study also can be helpful to many cities that wish to establish and implement the congestion pricing policy in practice.

Research on disruption management of urgent arrival in job shop with deteriorating effect

2021 ◽  
pp. 1-13
Author(s):  
Ning Tao ◽  
Duan Xiaodong ◽  
An Lu ◽  
Gou Tao
Keyword(s):  
Prospect Theory ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Quantum Particle ◽  
Particle Swarm ◽  
Cumulative Prospect Theory ◽  
Disruption Management ◽  
Particle Swarm Algorithm ◽  
Shop Scheduling ◽  
Management Method

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.

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