Ranking approach of cross-efficiency based on improved TOPSIS technique

The cross-efficiency evaluation method is reviewed which is developed as a data envelopment analysis （DEA） extensive tool. The cross-efficiency evaluation method is utilized to identify the decision making unit （DMU） with the best practice and to rank the DMUs by their respective cross-efficiency scores. The main drawbacks of the cross-efficiency evaluation method when the ultimate average cross-efficiency scores are used to evalu- ate and rank the DMUs are also pointed out. With the research gap, an improved technique for order preference by similarity to ideal solution （TOPSIS） is introduced to rank the crossfficiency by eliminating the average assumption. Finally, an empirical example is illustrated to examine the validity of the proposed method.

Extension of TOPSIS for fuzzy multi-attribute decision making problem based on experimental analysis

This paper is concerned with a technique for order performance by similarity to ideal solution（TOPSIS） method for fuzzy multi-attribute decision making,in which the information about attribute weights is partly known and the attribute values take form of triangular fuzzy numbers.Considering the fact that the triangular fuzzy TOPSIS results yielded by different distance measures are different from others,a comparative analysis of triangular fuzzy TOPSIS ranking from each distance measure is illustrated with discussion on standard deviation.By applying the most reasonable distance,the deviation degrees between attribute values are measured.A linear programming model based on the maximal deviation of weighted attribute values is established to obtain the attribute weights.Therefore,alternatives are ranked by using TOPSIS method.Finally,a numerical example is given to show the feasibility and effectiveness of the method.

TOPSIS with Belief Structure for Group Belief Multiple Criteria Decision Making

The technique for order performance by similarity to ideal solution （TOPSIS） is one of the major techniques in dealing with multiple criteria decision making （MCDM） problems, and the belief structure （BS） model has been used successfully for uncertain MCDM with incompleteness, impreciseness or ignorance. In this paper, the TOPSIS method with BS model is proposed to solve group belief MCDM problems. Firstly, the group belief MCDM problem is structured as a belief decision matrix in which the judgments of each decision maker are described as BS models, and then the evidential reasoning approach is used for aggregating the multiple decision makers＇ judgments. Subsequently, the positive and negative ideal belief solutions are defined with the principle of TOPSIS. To measure the separation from ideal solutions, the concept and algorithm of belief distance measure are defined, which can be used for comparing the difference between BS models. Finally, the relative closeness and ranking index are calculated for ranking the alternatives. A numerical example is given to illustrate the proposed method.

Importance Analysis on Subsystem of CNC Lathe Based on TOPSIS

An importance analysis model for computer numerical control（CNC）lathe subsystems was proposed.The model was based on technique for order preference by similarity to an ideal solution（TOPSIS）and considered the structure correlation between subsystems and the complete machine,the fault correlation of each subsystem and so on.The model can obtain a comprehensive sequencing of subsystems based on their importance to the complete machine.It lays a theoretical foundation for reliability allocation.

往复泵制造企业配件供应商选择的一种多属性决策方法

往复泵制造企业对配件供应商的选择是一个重要的决策问题。科学合理的评价和选择方法是做出正确决策的保证。提出了一种基于逼近理想解排序法(TOPSIS)和特征向量法的往复泵配件供应商选择方法,即使用特征向量法来确定指标权重,采用TOPSIS法对配件供应商做出选择。该方法提高了评价过程的科学性且便于操作,为解决往复泵制造企业配件供应商选择的多属性决策问题提供了良好的途径。最后通过实例验证了该方法的有效性。

Optimizing Rank of Landscape Planning Works of Urban Wetland Park

Classifying and ranking the huge amounts of landscape planning works of urban wetland park is always difficult due to the multi-functions （ecological, leisure, educational and disaster prevention） of the urban wetland park. Therefore, an optimizing rank system is urgently needed. Analytic Hierarchy Process （AHP） and Technique for Order Preference by Similarity to Ideal Solution （TOPSIS） models were used to rank the planning works of 30 urban wetland park based on four mainly factors, which included landscape ecological planning, landscape planning, ecological planning and economic planning. The study indicated that the AHP- TOPSIS model had good discrimination in the classification and ranking of landscape planning works of urban wetland park and it was also applicable to the planning works of other urban greenbelts.

Application of multi-criteria decision making methods for selection of micro-EDM process parameters

Ti-6A1-4V super alloy is an important engi- neering material with good strength to weight ratio and a wide range of applications in a number of engineering fields because of its excellent physical and mechanical properties. This work determines optimum process parameters such as pulse on time, peak current, gap voltage and flushing pressure, which influence the micro-electro discharge machining （EDM） process during machining of Ti-6AI-4V using combined methods of response surface methodology （RSM） and fuzzy-technique for order pref- erence by similarity to ideal solution （TOPSIS）. Central composite design （CCD） is used in the experimental investigation. A decision making model is developed to identify the optimum process parameters in the micro- EDM process, which influences several machining criteri- ons such as material removal rate （MRR）, tool wear rate （TWR）, overcut （OC） and taper. Triangular fuzzy numbers are used to determine the weighting factor for each process criterion. Further a fuzzy-TOPSIS method is used to select the most desirable factor level combinations. The proposed technique can be used to select optimal process parameters from various sets of combinations of process parameters in a micro-EDM process.