scholarly journals The Performance Evaluation of China Railway Corporation Modern Logistics Based on Combination Weighting Method and TOPSIS Method

2015 ◽  
Author(s):  
Bin Feng ◽  
Siping Qin
Keyword(s):  
Performance Evaluation ◽  
Topsis Method ◽  
Modern Logistics ◽  
Weighting Method ◽  
China Railway ◽  
Combination Weighting Method

scholarly journals Identifying key node in multi-region opportunistic sensor network based on improved TOPSIS

2021 ◽  
pp. 19-19
Author(s):  
Linlan Liu ◽  
Wei Wang ◽  
Guirong Jiang ◽  
Jiang Zhang
Keyword(s):  
Graph Model ◽  
Topsis Method ◽  
Weighting Method ◽  
Identification Methods ◽  
Subjective Weight ◽  
Dynamic Topology ◽  
The Game Theory ◽  
Novel Method ◽  
Topology Information ◽  
Combination Weighting Method

The topology of multi-region opportunistic sensor networks is evolving, and it is difficult to identify the key nodes in the networks by traditional key node identification methods. In this paper, a novel method based on the improved TOPSIS method is proposed to identify the key node from the ferry node. The dynamic topology information is represented by the graph model which is modeled by the temporal reachable graph. Based on the temporal reachable graph, three attributes are constructed to identify the key node, which are average degree, betweenness centrality and message forwarding rate. The game theory with a combination weighting method is employed to combine the subjective weight and objective weight, so as to obtain the combined weight of each attribute. The TOPSIS method is improved by the combined weight. The key node is identified by the improved TOPSIS. The experiments in three simulation situations show that, compared with the TOPSIS method and MADM_TOPSIS method, the proposed method has better accuracy for the key node identification in the network.

scholarly journals Performance Evaluation of Energy Research Projects Using DEA Super-Efficiency

Energies ◽  
2020 ◽  
Vol 13 (20) ◽  
pp. 5318
Author(s):  
Sungsig Bang
Keyword(s):  
Performance Evaluation ◽  
Research Performance ◽  
Data Envelopment ◽  
Research Projects ◽  
Performance Score ◽  
Energy Research ◽  
Weighting Method ◽  
Super Efficiency ◽  
Ranking Information ◽  
Research Performance Evaluation

This study proposes super efficiency (SE) as an efficient analytical method for evaluating the performance of energy research projects. Because the SE method is based on data envelopment analysis (DEA), it is free from the difficulty of weighting output, allows for the use of variables with diverse standards of measurement, and is capable of providing ranking information that regular DEA (CCR, BCC) analysis techniques cannot. To analyze the feasibility of the DEA-SE method, an efficiency evaluation was performed for energy research projects using both the weighting method as an existing method and the SE method. When the results were compared and analyzed, skewing toward particular output types was observed in the weighting method, owing to problems inherent in the method itself and in the weighting of subordinate variables that make up the total performance score. Therefore, adopting DEA-SE will redress the known problems of the weighting method by minimizing the problems of weighting and skewing in outputs, enabling use of the input and output variables with diverse units and standards of measurement, and providing ranking information of research performance evaluation that is unobtainable with the existing DEA method.

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