Improved TOPSIS Method Research Articles

Reasonability Evaluation of Land Reclamation Using the Improved TOPSIS Method: A Case Study of Four Farms in Guangxi, South China

Taking Guangxi agriculture and cultivation state-owned Jinguang Farm, Qianjiang Farm, Xinxing Farm and Liangqi Farm as land reclamation cases studies, 16 evaluation indices were selected from four aspects, i.e., investment in land reclamation project, implementation intensity of land reclamation, land use structure, and efficiency output of land reclamation, to evaluate the reasonability of land reclamation in the project area. The improved TOPSIS method and obstacle degree model were used to evaluate reasonability and diagnose obstacle factors. Results showed that the efficiency output of land reclamation had the greatest impact on its reasonability, followed by land use structure, with investment of land reclamation project having the least impact. The index obstacle factors mainly referred to the improved value of land quality. Through analysis of the evaluation results, the reasonability and obstacle factors of land reclamation were objectively determined to provide a reference for land reclamation in practice.

Traffic Performance Quality Level Classification and Evaluation of Road Network Planning Based on Improved TOPSIS Method

Traffic Performance Quality Level Classification and Evaluation of Road Network Planning Based on Improved TOPSIS Method

A novel improved TOPSIS method and its application in medical science

The TOPSIS method is a static comprehensive evaluation method for wide range applications. However, it encounters the reverse order problem in practical applications. Moreover, its evaluation value Ci only reflects the relative proximity of each evaluation object inside but not to the degree of closeness to the ideal optimal solution. The evaluation value is also limited to distinguish between the ranges of merit ranking. Since TOPSIS method has the wide range of applications, it is necessary to overcome the drawbacks of TOPSIS method. This article proposes a new improved TOPSIS method, which shows strict isotonicity and is more sensitive than the traditional TOPSIS method. The medical application based on this improved TOPSIS method is introduced.

Low-Carbon Economic Benefits Evaluation for Power Generation Projects with Improved TOPSIS Method Based on Combination Weighting

In the context of the low-carbon economy, economic benefits evaluations for power generation projects focus on the financial benefits and emphasize on the benefit from carbon-emission reduce. Thus, this paper firstly built an economic benefits evaluation index system for power generation projects based on low-carbon financial benefits and carbon-emission reduction efficiency. Then, it established an improved TOPSIS evaluation model based on orthogonal projection method and combination weighting which is determined by AHP subjectively and variation coefficient method objectively. Finally, the empirical analysis of wind power projects’ constructions verified the feasibility and effectiveness of the evaluation model using that new method.

The Application of the Improved TOPSIS Method in Bid Evaluation of Highway Construction

By analysising the disadvantages of the current bid evaluation methods used in highway project,the article builds up TOPSIS model based on coefficient of entropy to evaluating bidding units. First,the weight of each index is calculated by means of entropy weight coefficient method. Then it makes comprehensive assessment about bid evaluation with entropy weight coefficient method and TOPSIS method. The proposed method is applied to evaluating information system integration solutions and satisfactory results are abtained.

Evaluation for Survivable Networked System Based on Grey Correlation and Improved TOPSIS

Survivability has been one of the active fields in network security recently. In order to evaluate the survivability of networked system effectively, this paper proposes a method of combining grey correlation analysis and improved TOPSIS for quantitative assessment. Firstly, it normalizes indicator matrix according to improved TOPSIS method and determines the positive and negative ideal solutions. Secondly, it calculates correlation degree of every essential service in terms of grey correlation analysis, according to which with weight matrix, it gets the optimal dependency degree. Then it evaluates the whole survivability of networked system depending on the survivable function. At last the simulation and experimental results show the method is reasonable and effective.