Geological adaptability matching design of disc cutter using multicriteria decision making approaches

Geological adaptability matching design of a disc cutter is the prerequisite of cutter head design for tunnel boring machines(TBMs)and plays an important role in improving the tunneling efficiency of TBMs.The main purpose of the cutter matching design is to evaluate the cutter performance and select the appropriate cutter size.In this paper,a novel evaluation method based on multicriteria decision making(MCDM)techniques was developed to help TBM designers in the process of determining the cutter size.The analytic hierarchy process(AHP)and matter element analysis were applied to obtaining the weights of the cutter evaluation criteria,and the fuzzy comprehensive evaluation and technique for order performance by similarity to ideal solution(TOPSIS)approaches were employed to determine the ranking of the cutters.A case application was offered to illustrate and validate the proposed method.The results of the project case demonstrate that this method is reasonable and feasible for disc cutter size selection in cutter head design.

基于MCDM-BPNN的城市内涝风险评价及调蓄池选址

为建立一套较为完善的城市内涝风险评价体系,并据此确定调蓄池位置,首先,从积水风险、超载风险和边侧进流量3个维度构建评价指标,设计一种包括改进层次分析法(IAHP)、反熵权法(AEW)和优劣解距离法(TOPSIS)的混合多准则决策框架(MCDM);然后,将IAHP-AEW-TOPSIS模型分别与IAHP-TOPSIS、AEW-TOPSIS模型对比,通过斯皮尔曼排序相关系数验证排序一致性,通过计算变异系数、相对极差和灵敏度证实IAHP-AEW-TOPSIS模型的性能;最后,结合反向传播神经网络(BPNN),建立MCDM-BPNN模型,并以山西省某一内涝易发区域为例进行验证。结果表明:积水风险对城市内涝风险评价体系的影响最为显著,所占权重为0.46,其次为超载风险,所占权重为0.36;节点位置与连接管道数量很大程度上对该节点的内涝风险产生影响,在管道汇接处或汇流面积较大处内涝出现更为频繁;IAHP-AEW-TOPSIS模型在样本判别方面具有更好的性能;在5年与10年重现期下,MCDM-BPNN模型验证集准确率分别为93.3%和100%,能够准确快速模拟和预测城市洪水;应用案例设置调蓄池后,高、中、低风险节点数量分别为7、9、30和6、19、21,内涝溢流削减效果显著。

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.

A Quantity Model for Controlling and Measuring Software Quality Based on the Expert Decision-Making Algorithm

Researchers have been active in the field of software engineering measurement over more than 30 years. The software quality product is becoming increasingly important in the computerized society. Target setting in software quality function and usability deployment are essential since they are directly related to development of high quality products with high customer satisfaction. Software quality can be measured as the degree to which a particular software program complies with consumer demand regarding function and characteristics. Target setting is usually subjective in practice, which is unscientific. Therefore, this study proposes a quantity model for controlling and measuring software quality via the expert decision-making algorithm-based method for constructing an evaluation method can provide software in relation to users and purchasers, thus enabling administrators or decision makers to identify the most appropriate software quality. Importantly, the proposed model can provide s users and purchasers a reference material, making it highly applicable for academic and government purposes.

基于多准则决策方法的避难场所选址模型研究

针对避难场所规划选址中的现实问题与需求,从方法易操作和可实施角度出发,构建了面向城市规划业务流程与工作实践的防灾避难场所选址模型。该模型基于多准则决策方法(MCDM),以避难场所选址的安全性和均好性为主要目标。模型综合考虑了人口密度、建筑质量、交通系统和避难场所设施配置四项选址影响因素,并采用AHP-熵权法确定影响要素权重。以江阴市为实证案例,套用模型经过两轮评估及编码者测试,最终明确了备选避难场所资源的优先建设排序,验证了模型的可行性与实用性。研究提出的影响要素和量化指标易于取得,打分方法便于操作,适用于城市规划阶段的避难场所规划选址与建设时序决策。

考虑性能稳定性的机械系统可靠性分配方法研究

针对机械系统可靠性分配,提出了一种考虑性能稳定性的可靠性分配方法。引入元动作理论对机械系统进行结构分解,以元动作单元为分配对象,建立元动作可靠性二层综合评价指标模型,结合多准则决策(MCDM)方法,得到元动作可靠性分配系数;然后建立机械传动系统稳定性模型,并计算各个元动作对系统性能稳定性的影响系数;最后,利用性能稳定性的影响系数对可靠性分配系数进行修正,实现机械系统可靠性的合理分配。通过与传统方法进行对比,验证了所提方法的有效性。

煤矿生产物流系统安全资源DMIP-MCDM评价法

为提升煤矿生产物流系统安全水平,运用多准则决策(MCDM)方法,建立基于动态多维交互投影(DMIP)的煤矿生产物流系统安全资源DMIP-MCDM评价法。首先,集成多个直觉正态模糊数(INFNs)动态聚合决策矩阵,并由此计算初始评价权重及均衡度评价权重;其次,依托直觉正态模糊广义混合变权Bonferroni(INFNGHVWB)算子计算精确度评价权重;再次,计算各级指标因素层的DMIP聚合评价权重及安全资源配置的最终总体评价权重;最后将DMIP-MCDM评价法应用于某矿生产物流系统中,进行实证分析。结果表明,安全资源配置的类别各异,同时交互影响;用DMIPMCDM能够实现安全资源配置状况的多维动态系统评价,有助于优化安全资源配置结构。

基于FBWM-TOPSIS的配电网检修关键线路识别方法

在有限的资源和时间背景下,设备检修是保持系统稳定运行的有效方法。为了高效地分配检修资源,应该首先确定系统中最关键的设备,即那些发生故障会造成较大后果的设备。首先提出了一种新的多准则决策方案来识别配电网中的关键线路,与以往基于层次分析法不同,采用最优-最劣法,根据专家的知识和判断求得系统可靠性指标的权重。此外,在传统最优-最劣法中引入模糊理论克服专家判断和决策中普遍存在的不确定性。最后,利用逼近理想解排序法对IEEE14节点配电网线路进行检修优先排序。所提的方法可以更快、更准确地确定系统检修的优先顺序。

Novel Scheme for Essential Proteins Identification Based on Improved Multicriteria Decision Making

Identifying essential proteins from protein-protein interaction networks is important for studies onbiological evolution and new drug’s development.Most of the presented criteria for prioritizing essential proteinsonly focus on a certain attribute of the proteins in the network,which suffer from information loss.In order toovercome this problem,a relatively comprehensive and effective novel method for essential proteins identificationbased on improved multicriteria decision making(MCDM),called essential proteins identification-technique fororder preference by similarity to ideal solution(EPI-TOPSIS),is proposed.First,considering different attributes ofproteins,we propose three methods from different aspects to evaluate the significance of the proteins:gene-degreecentrality(GDC)for gene expression sequence;subcellular-neighbor-degree centrality(SNDC)and subcellular-indegree centrality(SIDC)for subcellular location information and protein complexes.Then,betweenness centrality(BC)and these three methods are considered together as the multiple criteria of the decision-making model.Analytic hierarchy process is used to evaluate the weights of each criterion,and the essential proteins are prioritizedby an ideal solution of MCDM,i.e.,TOPSIS.Experiments are conducted on YDIP,YMIPS,Krogan and BioGRIDnetworks.The results indicate that EPI-TOPSIS outperforms several state-of-the-art approaches for identifyingthe essential proteins through the performance measures.

A Hybrid MCDM Approach Based on ANP and TOPSIS for Facility Layout Selection

Facility layout selection is a multi-criteria decision making (MCDM) problem,since it has a strategic impact on the efficiency of manufacturing system.In view of the interdependency among selection criteria,analytic network process (ANP) is proposed to analyze the structure of the facility layout selection problem and determine the weights for each criterion.A network structure is constructed that shows all elements and clusters and their interactions.Limit priorities are also calculated which help decision maker evaluate the relative importance among criterion in the alternative selection process.Moreover,a hybrid MCDM approach that employs ANP and technique for order preference by similarity to an ideal solution (TOPSIS)method to rank the optimal facility layout alternatives.Finally,an application of a new aeronautic component assembly workshop facility layout selection is conducted.To further illustrate the advantage of the proposed approach,the difference between ANP-TOPSIS and AHP-TOPSIS methods are compared and discussed.Results have demonstrated the effectiveness and feasibility of the proposed method.

Robust data envelopment analysis based MCDM with the consideration of uncertain data

The application of data envelopment analysis （DEA） as a multiple criteria decision making （MCDM） technique has been gaining more and more attention in recent research. In the practice of applying DEA approach, the appearance of uncertainties on input and output data of decision making unit （DMU） might make the nominal solution infeasible and lead to the efficiency scores meaningless from practical view. This paper analyzes the impact of data uncertainty on the evaluation results of DEA, and proposes several robust DEA models based on the adaptation of recently developed robust optimization approaches, which would be immune against input and output data uncertainties. The robust DEA models developed are based on input-oriented and outputoriented CCR model, respectively, when the uncertainties appear in output data and input data separately. Furthermore, the robust DEA models could deal with random symmetric uncertainty and unknown-but-bounded uncertainty, in both of which the distributions of the random data entries are permitted to be unknown. The robust DEA models are implemented in a numerical example and the efficiency scores and rankings of these models are compared. The results indicate that the robust DEA approach could be a more reliable method for efficiency evaluation and ranking in MCDM problems.

Transformation and risk assessment of the East Kolkata Wetlands (India)using fuzzy MCDM method and geospatial technology

The East Kolkata Wetlands (EKW) is located on the eastern periphery of the city of Kolkata and extends up to theBidyadhari-Matla River confluence. It is a Ramsar Site and acts as an absorber basin for a large number of con-taminants drained from Kolkata. Agricultural lands, sewage-fed fisheries, garbage dumping fields, horticulture,and built-up areas are included in this protected area, that covers approximately 125 km2. It reveals that climatechange reduces the variety of wetland ecosystem services and increases socio-economic vulnerability and eco-nomic stress. The human encroachment, reclamation of land for agriculture, aquaculture, and urban expansion inand around Kolkata has recently adversely threatened the EKW. The remotely sensed data, socio-economic data,and responses of inhabitants have been used to analyse the EKW’s risk and vulnerability. We employed geospatialanalysis by using the Multi-Criteria Decision Making (MCDM) method using nine risk factors. An in-depth analysisof the EKW using geospatial techniques and the Fuzzy Analytic Hierarchy Process (FAHP) helped to understandthe EKW transformations through vulnerability and risk analysis. The results show that the transformation of thewetland to aquaculture, eutrophication and pollution, road proximity, waste dumping, population density, andgrowth are the main factors for the deteriorating health, quality, and environment of the EKW. It also reveals thatquantitative and qualitative evaluations of ecosystem services, wetland degradation, transformation, and cause-effect rapport should be periodically assessed using scientific methods like FAHP, RS, GIS to formulate resilient,integrated plans and strategy for the sustainable management of the EKW.

基于广义正交三角模糊数的WSM-TOPSIS群决策方法

结合广义正交模糊集和三角直觉模糊数,给出广义正交三角模糊数的定义和运算法则,在此基础上,对WSM和TOPSIS方法进行拓展,提出一种多属性群决策方法WSM-TOPSIS。考虑到决策者和属性的权重,该方法使用WSM对决策者提出的决策矩阵进行第一次集结,通过TOPSIS计算各方案的相对贴近度得到方案的优劣排序。最后通过实例和对比分析验证了该方法的有效性和实用性。

Novel Scheme for Robust Confusion Component Selection Based on Pythagorean Fuzzy Set

The substitution box,often known as an S-box,is a nonlinear component that is a part of several block ciphers.Its purpose is to protect cryptographic algorithms from a variety of cryptanalytic assaults.A Multi-Criteria Decision Making(MCDM)problem has a complex selection procedure because of having many options and criteria to choose from.Because of this,statistical methods are necessary to assess the performance score of each S-box and decide which option is the best one available based on this score.Using the Pythagorean Fuzzy-based Technique for Order of Preference by Similarity to Ideal Solution(TOPSIS)method,the major objective of this investigation is to select the optimal S-box to be implemented from a pool of twelve key choices.With the help of the Pythagorean fuzzy set(PFS),the purpose of this article is to evaluate whether this nonlinear component is suitable for use in a variety of encryption applications.In this article,we have considered various characteristics of S-boxes,including nonlinearity,algebraic degree,strict avalanche criterion(SAC),absolute indicator,bit independent criterion(BIC),sum of square indicator,algebraic immunity,transparency order,robustness to differential cryptanalysis,composite algebraic immunity,signal to noise ratio-differential power attack(SNR-DPA),and confusion coefficient variance on some standard S-boxes that are Advanced Encryption Following this,the findings of the investigation are changed into Pythagorean fuzzy numbers in the shape of a matrix.This matrix is then subjected to an analysis using the TOPSIS method,which is dependent on the Pythagorean fuzzy set,to rank the most suitable S-box for use in encryption applications.

属性值为区间数的决策对象预期理论模型研究

针对属性值为区间数的多属性决策中不同区间数相互比较具有相同可能度的问题进行研究。根据决策者不同的风险偏好将其分为3类,对不同风险偏好类型的决策者提出相应的预期理论模型,确定区间数之间的优势关系。在此基础之上,提出决策对象优势关系及优势度矩阵,并根据优势度数值对决策对象进行排序择优。最后,通过实例验证新排序算法的科学性与有效性。

基于FAHP的应急物流外包供应商绩效综合评价

考虑到决策者决策的模糊特征,提出一种权重向量和属性变量都是三角模糊数的模糊层次分析法,并把该方法引入到应急物流外包供应商的绩效评价领域.根据三角模糊数的有关理论,得到三角模糊数判断矩阵、权重向量和综合评价值的计算方法,使得评价信息能更加合理地反映实际.同时,提出一种具有决策者风险偏好的三角模糊数的排序方法.最后,实例分析结果表明该方法具有实用性,其评价结果可以给决策者提供一个适当的方法来选择最优的应急物流外包供应商.

基于Vague集模糊多准则决策记分函数法改进性探讨

分析现有的两种基于V ague集记分函数法在决策时存在的局限性与不一致性。针对局限性,提出了一种新的基于反对程度的辅助记分函数,通过运用这一辅助记分函数保证了在以上两种记分函数法无法决策时能够提供一种更为精确的决策方法;针对决策的不一致性,提出了应选择的决策策略。

基于多指标决策的武器装备作战效能综合评估

综合评述了作战效能评估方法,分析了各种方法的适用范围并对比了其优劣。根据作战效能的特点与系统工程思想,提出了基于多指标决策的武器装备作战效能评估模型。针对作战指标的相对性、模糊性和灰色性,运用灰色关联投影法定量计算得到武器装备作战效能的综合评估值,并依此对武器装备进行排序。通过3种型号潜射鱼雷的实例验证了该模型和算法的工程实用性,其评估结果表明该方法比模糊关联法和灰色关联法更有效。

基于区间二元语义VIKOR的外包供应商选择模型

在外包战略中,间接成本提升、信息不对称、控制权降低等问题给供应商选择增加了困难.为充分发挥外包优势、降低外包风险,将外包供应商选择准则分为服务质量、价格与成本、沟通与协调以及研发与创新四类,并运用区间二元语义VIKOR模型对外包供应商进行评价及排序.通过算例及比较分析验证了区间二元语义VIKOR模型在外包供应商选择中的优势.结果显示所提出模型不仅有效避免了数据处理过程中信息失真情况,规避了排序结果重复的问题,而且可同时处理定性与定量数据,融入了主客观权重及决策者偏好,从而为企业选择供应商提供了更为理想的方法.

产品方案优选的区间二型模糊VIKOR法

由于传统一型模糊集的隶属度难以给出精确值,因此采用区间二型模糊集理论对VIKOR方法进行扩展从而建立产品方案的决策优选模型。首先介绍了区间二型模糊数的概念,并结合积分法和区间模糊数比较法定义了一种排序方法,在此基础上实现传统VIKOR算法的扩展。为保证信息的准确性、有效性,在扩展VIKOR算法的整个过程中都未使用解模糊技术,而始终保持评估值的模糊性。产品最优方案根据VIKOR综合指标的排序来选择,其中"群体效益"和"最大个别遗憾"的决策权重由决策者偏好决定。最后,以轨道车辆门产品的方案评价为例,证明所提方法的可行性和有效性。