scholarly journals Location Selection of Express Distribution Centre with Probabilistic Linguistic MABAC Method Based on the Cumulative Prospect Theory

Informatica ◽  
2022 ◽  
pp. 1-20
Author(s):  
Siqi Tang ◽  
Guiwu Wei ◽  
Xudong Chen
Keyword(s):  
Prospect Theory ◽  
Cumulative Prospect Theory ◽  
Location Selection ◽  
Distribution Centre ◽  
Selection Of

Optimal selection of energy storage nodes based on improved cumulative prospect theory in China

2020 ◽  
Vol 12 (6) ◽  
pp. 064101
Author(s):  
Jicheng Liu ◽  
Zhenzhen Wang ◽  
Yu Yin ◽  
Yinghuan Li ◽  
Yunyuan Lu
Keyword(s):  
Energy Storage ◽  
Prospect Theory ◽  
Cumulative Prospect Theory ◽  
Optimal Selection ◽  
Selection Of

scholarly journals Extended GRA Method Based on Cumulative Prospect Theory with Probabilistic Hesitant Fuzzy Information for MAGDM and its Application to Green Supplier Selection

2021 ◽  
Author(s):  
Ningna Liao ◽  
Guiwu Wei ◽  
Xudong Chen
Keyword(s):  
Prospect Theory ◽  
Simulation Analysis ◽  
Cumulative Prospect Theory ◽  
Decision Makers ◽  
Risk Appetite ◽  
Probabilistic Values ◽  
Grey Relational ◽  
Decision Elements ◽  
Different Levels ◽  
Selection Of

Abstract An extended grey relational analysis (GRA) method is introduced in this article to reduce the limitations of the classical GRA method using the cumulative prospect theory (CPT) which takes into account psychological factors such as the risk appetite of decision makers. Moreover, the circumstance of probabilistic hesitant fuzzy (PHF) which assigns probabilistic values to DMs’ different levels of hesitation shows its superiority when making decisions in a complex environment. Meanwhile the weighting vector of each attribute is calculated according to the entropy which is calculated by the different prospect decision elements. Thus, in this paper, we proposed an extended GRA method based on cumulative prospect theory in the probabilistic hesitant fuzzy circumstance and applying the model in the selection of the green supplier. At last, the comparative analysis and the simulation analysis are made to show the practicability of this newly proposed method.

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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