To solve the expression difficulties resulting from variety of random sample spaces in decision network planning, an expanded decision unit structure including several sample spaces was presented. 为解决决策网络计划中随机样本空间变化而产生的模型表达上的困难,提出经拓展能够描述多个样本空间的决策单元结构。
It is permissible to call the smallest quantity which can be the object of such a decision a unit. 我们可以把那作为选择对象的最小量叫做一个单位。
A fuzzy-based model for estimating the parameters ( or boundary values) in each decision unit is also presented. 文中还给出了用来辨识认知网络未知参数(边界值)的模糊数学规划模型。
First, uses the thought of matter element extension determine set of decision unit and collect quantity information. 用物元的发散性思想找到与待决策单元同名、同值、同征的单元并收集它们的数量信息;
Secondly, gives select method of decision unit by using AHP. 其次,用层次分析方法给出了待决策单元标杆的选择方法;
A Method on Minimizing the Sum of Deviations to Transform Decision Making Unit into DEA Efficient 使决策单元变为DEA有效的偏差和最小法
C2R model which was firstly introduced and widely used can decide whether the DMU ( Decision Making Unit) come to technological efficiency and scale efficiency at the same time or not. 其最先提出并被广泛应用的C2R模型可同时判断决策单元是否同时满足技术有效和规模有效。
A method on making decision making unit DEA efficient 使决策单元变为DEA有效的一种方法
For the mixed model in DEA discussed in reference 1, this paper studies its sensitivity analysis. Sufficient condition for simultaneous change of all outputs and all inputs of an efficient decision making unit which preserves efficiency are established. 对文献〔1〕所讨论的混合的DEA模型,进行灵敏度分析,对原来DEA有效的决策单元给出了在改变其输入与输出后仍保持DEA有效的充分条件。
Efficient Decision Making Unit on Technical Efficiency and DEA Efficiency ( C~ 2GS~ 2) 技术有效的决策单元与DEA有效性(C~2GS~2)
The paper proves that for given decision making unit its weak DEA efficiency or DEA efficiency can be judged by the optimal solution of the cost minimization problem under some conditions on the basis of reference [ 1]. 在文[1]的基础上,本文证明了在一定条件下对所给的决策单元、其弱DEA有效性或DEA有效性能由成本最小问题的最优解来判断。
In this paper, we obtained two new sufficient and necessary conditions for DEA efficiency ( M) of a decision making unit. On the basis of them, the sensitivity analysis of the mixed model in DEA is discussed. 本文给出了有关决策单元为DEA有效(M)的充要条件的两个新定理,在这基础上讨论了混合的DEA模型的灵敏度分析。
Data Envelopment Analysis ( DEA) is a mathematical programming approach, which has been widely accepted as an effective tool to evaluate the efficiency of a Decision Making Unit ( DMU) relative to other DMUs. 数据包络分析(DEA)作为一种数学规划方法,已经被广泛用来评价一个决策单元相对于其它决策单元的效率。
A new population consists of excellent ones of each evolved sub-population and is evolved within the whole search space, and at last, corresponding actions are taken based on the results by the decision unit. 在子伤务完成后,各子群中的优秀分子组成新的种群,在整个问题空间完成进化,然后由决定机构根据情况选择相应的可能行动。
On the study of system evaluation approach today, each decision unit is commonly regarded as one object and selected by evaluation institution, which is not reality because of the absence of rivalry. 在现今的系统评估方法研究中,通常把每一决策单元,即被评估者看成一种客体,被动地由评估者进行优选,缺乏竞争性,往往与现实不符。
We also define the actual efficiency ratio of DEA efficient decision unit within the C~ 2RM model, and eventually get a kind of taxis for all decision unit s. In the end we give an example to illustrate it. 在优势集性质基础上我们进一步定义了C2RM模型下DEA有效决策单元的实际有效率,并给出了所有决策单元的一种排序,最后举例予以说明。
A Discussion on the Assessed Decision Making Unit in DEA 对数据包络分析中被评价的决策单元的探讨
The mechanism of the model is to take a logistics activity as a decision making unit to evaluate the efficiency of input and output. 该模型的运行机理是用DEA方法将物流作业作为决策单元评价输入输出要素的运作效率。
This paper mainly studies sensitivity analysis of G~ 2GS~ 2 model in data envelope analysis, and presents sufficient conditions for simultaneous change of all inputs and all outputs of an efficient decision making unit which preserves efficiency. 本文主要趼究数据包络分析中C~2GS~2模型的灵敏度分析,提出了有效决策单元在其投入产出发生变化时,保持其有效性不变的条件。
Furthermore it analyzes decision making unit's feature of distribution, projection property and model definition in the sample possible set. 进而,分析了决策单元在样本可能集中的分布特征、投影性质和模型含义等问题。
Stochastic frontier analysis is an effective method to analyze the efficiency of Decision Making Unit ( DMU), but the decomposition of the error term is difficult, the research aims at searching for concise and efficient algorithm. 随机前沿面模型是评价决策单元投入产出效率的重要方法之一,但模型中参数的求解和误差项的分解比较困难,寻求简洁有效算法是研究的重点。
The customer satisfactory degree is evaluated by combining fuzzy theory with DEA method. The customers need only to work out their own fuzzy conclusions. And the weight "input" and "output" of every decision marking unit is calculated with the actual data. 将模糊理论与DEA方法相结合评价顾客满意度,顾客只需作出自己的模糊印象结论,而每个决策单元的输入和输出的权重由其实际数据求得。
On this basis construct a multi-department joint meeting decision-making model, it concludes Joint Meeting decision-making Service Platform, Joint Meeting Decision-making control Model, Decision Element Unit Components. 在此基础上我们构建了联席决策模型,该模型包括联席决策服务平台、联席决策控制模型、决策元部件几部分。
This thesis will firstly apply Window analysis of DEA model on evaluating the efficiency of the port, select 2001-2010 data of the Qingdao Port as the study sample, and create 6 Decision Making Unit ( DMU). 本文首先将时间窗口DEA模型运用到港口效率评价中,选择青岛港2001-2010年数据为研究样本,共创建6个决策单元。
It can not only measure the efficiency of each decision making unit ( DMU) objectively, but also improve the inefficient DMUs by projection. 这不仅仅因为它能客观地度量各决策单元的效率,还因为它能通过投影的方式对效率低下的决策单元进行改进。
So a decision unit structure with several sample spaces is put forward. And a random optimization method, which considers expected cost and risk, is given. 为此,本文提出了能够表达多个样本空间的的决策单元结构,并将随机规划方法引入模型优化,建立了综合考虑期望成本和风险的随机优化方法。
Chapter V was the analysis of the case, it choose eight enterprises as the decision making unit that in the low-carbon supply chain to doing the performance evaluation. 第五章为案例分析,选取了位于低碳绿色供应链内部的八家企业作为决策单元进行绩效评价。
The advantage of this model is not only to integrate the preferences of decision maker, but also improve the technical level of the decision making unit in the organization. 该模型的优势不仅在于整合了管理者对行业的期望产出水平和减少污染排放水平的不同偏好,还同时改进了组织中各决策单元的技术水平。
Research from the most beneficial to evaluate the perspective of decision making unit, focusing on the optimization of each decision making unit, pointing out that the adjustment of the direction of the indicators. 研究从最有利于决策单元的角度进行评价,注重每一个决策单元的优化,指出有关指标的调整方向。
Traditional DEA method put decision unit as a "black box", do not consider decision unit the system structure, ignore system between neutron process, and the mutual influence the efficiency of system subprocesses efficiency the influence of overall efficiency. 传统DEA方法把决策单元看成一个黑箱,不考虑决策单元的系统构成,忽视系统中子过程之间效率的相互影响,以及子过程效率对系统整体效率的影响。