Risk decision analysis in emergency response: A method based on cumulative prospect theory

2014 ◽  
Vol 42 ◽  
pp. 75-82 ◽  
Author(s):  
Yang Liu ◽  
Zhi-Ping Fan ◽  
Yao Zhang
Keyword(s):  
Decision Analysis ◽  
Prospect Theory ◽  
Emergency Response ◽  
Cumulative Prospect Theory ◽  
Risk Decision

Decision Analysis with Cumulative Prospect Theory

2000 ◽  
Vol 20 (4) ◽  
pp. 404-411 ◽  
Author(s):  
Ahmed M. Bayoumi ◽  
Donald A. Redelmeier
Keyword(s):  
Decision Analysis ◽  
Prospect Theory ◽  
Cumulative Prospect Theory

scholarly journals Behavioral multi-criteria decision analysis: further elaborations on the todim method

2012 ◽  
Vol 37 (1) ◽  
pp. 3-8 ◽  
Author(s):  
Luiz Flavio Autran Monteiro Gomes ◽  
Xavier Ignacio González
Keyword(s):  
Decision Theory ◽  
Decision Analysis ◽  
Prospect Theory ◽  
Reference Point ◽  
Short Communication ◽  
Cumulative Prospect Theory ◽  
Behavioral Decision Theory ◽  
Behavioral Decision ◽  
Todim Method

Abstract.This short communication reviews the role of the TODIM method within behavioral decision theory and presents its genesis. Two important aspects of the method such as generalizing that method towards cumulative prospect theory and the choice of a reference point are further clarified.

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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