A Strategy of Gird Resource Utility Allocation Based on Shapley Value

2011 ◽  
Author(s):  
Qiongfen Qian ◽  
Chunlin Li ◽  
Xiaoqing Zhang ◽  
Hengxi Zhang
Keyword(s):  
Shapley Value ◽  
Utility Allocation

A novel q-rung orthopair fuzzy TODIM approach for multi-criteria group decision making based on Shapley value and relative entropy

2021 ◽  
Vol 40 (1) ◽  
pp. 235-250
Author(s):  
Liuxin Chen ◽  
Nanfang Luo ◽  
Xiaoling Gou
Keyword(s):  
Decision Making ◽  
Relative Entropy ◽  
Group Decision Making ◽  
Shapley Value ◽  
Group Decision ◽  
Similarity Measures ◽  
Entropy Measure ◽  
Shapley Values ◽  
Interactive Relationship ◽  
The Difference

In the real multi-criteria group decision making (MCGDM) problems, there will be an interactive relationship among different decision makers (DMs). To identify the overall influence, we define the Shapley value as the DM’s weight. Entropy is a measure which makes it better than similarity measures to recognize a group decision making problem. Since we propose a relative entropy to measure the difference between two systems, which improves the accuracy of the distance measure.In this paper, a MCGDM approach named as TODIM is presented under q-rung orthopair fuzzy information.The proposed TODIM approach is developed for correlative MCGDM problems, in which the weights of the DMs are calculated in terms of Shapley values and the dominance matrices are evaluated based on relative entropy measure with q-rung orthopair fuzzy information.Furthermore, the efficacy of the proposed Gq-ROFWA operator and the novel TODIM is demonstrated through a selection problem of modern enterprises risk investment. A comparative analysis with existing methods is presented to validate the efficiency of the approach.

Profit distribution of liner alliance based on shapley value

2021 ◽  
pp. 1-5
Author(s):  
Bin Guo ◽  
Shengyue Hao ◽  
Guangmei Cao ◽  
Honghu Gao
Keyword(s):  
Decision Making ◽  
Customer Satisfaction ◽  
Shapley Value ◽  
Case Analysis ◽  
Distribution Method ◽  
New Model ◽  
Profit Distribution ◽  
Scientific Decision ◽  
Stable Development

Profit distribution plays an important role in the sustainable and stable development of liner alliances, this paper tries to solve the profit distribution issues in the liner alliance based on Shapley Value Method. Meanwhile, seeing that there is little consideration from the customer satisfaction, this paper establishes a new model by revising Shapley Value Method to distribute the profit of liner alliances from the perspectives of suppliers and customers and carry out verification through case analysis. The profit distribution method proposed in the paper is helpful to the reasonable profit distribution of liner alliance. It ensures the continuity and stability of liner alliance and provides a scientific decision-making basis for the profit distribution of liner alliance.

Allocating Positions Fairly: Auctions and Shapley Value

2021 ◽  
pp. 105315
Author(s):  
Matt Van Essen ◽  
John Wooders
Keyword(s):  
Shapley Value

scholarly journals A Profit Distribution Model of Reverse Logistics Based on Fuzzy DEA Efficiency—Modified Shapley Value

2021 ◽  
Vol 13 (13) ◽  
pp. 7354
Author(s):  
Jiekun Song ◽  
Xiaoping Ma ◽  
Rui Chen
Keyword(s):  
Shapley Value ◽  
Reverse Logistics ◽  
Service Providers ◽  
Third Party ◽  
Output Data ◽  
Profit Distribution ◽  
Logistics Service ◽  
Input And Output ◽  
Value Model ◽  
Fuzzy Dea

Reverse logistics is an important way to realize sustainable production and consumption. With the emergence of professional third-party reverse logistics service providers, the outsourcing model has become the main mode of reverse logistics. Whether the distribution of cooperative profit among multiple participants is fair or not determines the quality of the implementation of the outsourcing mode. The traditional Shapley value model is often used to distribute cooperative profit. Since its distribution basis is the marginal profit contribution of each member enterprise to different alliances, it is necessary to estimate the profit of each alliance. However, it is difficult to ensure the accuracy of this estimation, which makes the distribution lack of objectivity. Once the actual profit share deviates from the expectation of member enterprise, the sustainability of the reverse logistics alliance will be affected. This study considers the marginal efficiency contribution of each member enterprise to the alliance and applies it to replace the marginal profit contribution. As the input and output data of reverse logistics cannot be accurately separated from those of the whole enterprise, they are often uncertain. In this paper, we assume that each member enterprise’s input and output data are fuzzy numbers and construct an efficiency measurement model based on fuzzy DEA. Then, we define the characteristic function of alliance and propose a modified Shapley value model to fairly distribute cooperative profit. Finally, an example comprising of two manufacturing enterprises, one sales enterprise, and one third-party reverse logistics service provider is put forward to verify the model’s feasibility and effectiveness. This paper provides a reference for the profit distribution of the reverse logistics.

Query Games in Databases

2021 ◽  
Vol 50 (1) ◽  
pp. 78-85
Author(s):  
Ester Livshits ◽  
Leopoldo Bertossi ◽  
Benny Kimelfeld ◽  
Moshe Sebag
Keyword(s):  
Game Theory ◽  
Cooperative Game ◽  
Shapley Value ◽  
Cooperative Game Theory ◽  
The Shapley Value ◽  
Computational Aspects ◽  
Aggregate Query ◽  
Boolean Query

Database tuples can be seen as players in the game of jointly realizing the answer to a query. Some tuples may contribute more than others to the outcome, which can be a binary value in the case of a Boolean query, a number for a numerical aggregate query, and so on. To quantify the contributions of tuples, we use the Shapley value that was introduced in cooperative game theory and has found applications in a plethora of domains. Specifically, the Shapley value of an individual tuple quantifies its contribution to the query. We investigate the applicability of the Shapley value in this setting, as well as the computational aspects of its calculation in terms of complexity, algorithms, and approximation.

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