Assessing Suitability of Rural Settlements Using an Improved Technique for Order Preference by Similarity to Ideal Solution

Land suitability assessment is a prerequisite phase in land use planning; it guides toward optimal land use by providing information on the opportunities and constraints involved in the use of a given land area. A geographic information system-based procedure, known as rural settlement suitability evaluation(RSSE) using an improved technique for order preference by similarity to ideal solution(TOPSIS), was adopted to determine the most suitable area for constructing rural settlements in different geographical locations. Given the distribution and independence of rural settlements, a distinctive evaluation criteria system that differed from that of urban suitability was established by considering the level of rural infrastructure services as well as living and working conditions. The unpredictable mutual interference among evaluation factors has been found in practical works. An improved TOPSIS using Mahalanobis distance was applied to solve the unpredictable correlation among the criteria in a suitability evaluation. Uncertainty and sensitivity analyses obtained via Monte Carlo simulation were performed to examine the robustness of the model. Daye, a resource-based city with rapid economic development, unsatisfied rural development, and geological environmental problems caused by mining, was used as a case study. Results indicate the following findings: 1) The RSSE model using the improved TOPSIS can assess the suitability of rural settlements, and the suitability maps generated using the improved TOPSIS have higher information density than those generated using traditional TOPSIS. The robustness of the model is improved, and the uncertainty is reduced in the suitability results. 2) Highly suitable land is mainly distributed in the northeast of the study area, and the majority of which is cultivated land, thereby leading to tremendous pressure on the loss of cultivated land. 3) Lastly, 12.54% of the constructive expansion permitted zone and 8.36% of the constructive expansion conditionally permitted zone are situated in an unsuitable area, which indicates that the general planning of Daye lacks the necessary verification of suitability evaluation. Guidance is provided on the development strategy of rural settlement patches to support decision making in general land use planning.

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.

Research on Network Maintenance Strategy Selection Based on Analytic Hierarchy Process and Technique for Order Preference by Similarity to Ideal Solution Algorithm

Network maintenance strategy selection is a multi-objective decision making topic. It mostly depends on the uncertainty and fuzziness of decision makers and conditions. In this paper, based on analytic hierarchy process(AHP) and technique for order preference by similarity to ideal solution(TOPSIS), TOPSIS partial order method is proposed to choose the optimal maintenance strategy. This method uses AHP to determine the weights of evaluation indexes. The optimal maintenance strategy choice is given as an example to demonstrate the effectiveness of the method.

A Decision Support System for Selection of Solar Power Plant Locations by Applying Fuzzy AHP and TOPSIS: An Empirical Study

The objective of this research is to propose a decision support system for avoiding flood on solar power plant site selection. Methodologically, the geographic information system (GIS) is used to determine the optimum site for a solar power plant. It is intended to integrate the qualitative and quantitative variables based upon the adoption of the Fuzzy Analytic Hierarchy Process (Fuzzy AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) model. These methods are employed to unite the environmental aspects and social needs for electrical power systematically. Regarding a case study of the choice of a solar power plant site in Thailand, it demonstrates that the quantitative and qualitative criteria should be realized prior to analysis in the Fuzzy AHP-TOPSIS model. The fuzzy AHP is employed to determine the weights of qualitative and quantitative criteria that can affect the selection process. The adoption of the fuzzy AHP is aimed to model the linguistic unclear, ambiguous, and incomplete knowledge. Additionally, TOPSIS, which is a ranking multi-criteria decision making method, is employed to rank the alternative sites based upon overall efficiency. The contribution of this paper lies in the evolution of a new approach that is flexible and practical to the decision maker, in providing the guidelines for the solar power plant site choices under stakeholder needs: at the same time, the desirable functions are achieved, in avoiding flood, reducing cost, time and causing less environmental impact. The new approach is assessed in the empirical study during major flooding in Thailand during the fourth quarter of 2011 to 2012. The result analysis and sensitivity analysis are also presented.

An Evaluation of the Critical Success Factors in Sustainable Food Supply Chains in Developing Countries

Food is one of the biggest industries in developed and underdeveloped countries. Supply chain sustainability is essential in established and emerging economies because of the rising acceptance of cost-based outsourcing and the growing technological, social, and environmental concerns. The food business faces serious sustainability and growth challenges in developing countries. A comprehensive analysis of the critical success factors (CSFs) influencing the performance outcome and the sustainable supply chain management (SSCM) process. A theoretical framework is established to explain how they are used to examine the organizational aspect of the food supply chain life cycle analysis. This study examined the CSFs and revealed the relationships between them using a methodology that included a review of literature, interpretative structural modeling (ISM), and cross-impact matrix multiplication applied in classification (MICMAC) tool analysis of soil liquefaction factors. The findings of this research demonstrate that the quality and safety of food are important factors and have a direct effect on other factors. To make sustainable food supply chain management more adequate, legislators, managers, and experts need to pay attention to this factor. In this work. It also shows that companies aiming to create a sustainable business model must make sustainability a fundamental tenet of their organization. Practitioners and managers may devise effective long-term plans for establishing a sustainable food supply chain utilizing the recommended methodology.

基于ANP-TOPSIS的煤矿风险预控管理体系有效性评估

风险预控管理体系的实施降低了煤矿事故的数量和死亡人数,但由于煤矿企业在实施此体系过程中存在着不科学性和不系统性等问题,导致对煤矿事故控制还没达到预期效果。因此,如何科学有效的评估当前煤矿风险预控管理现状显得尤为关键。通过构建基于网络层次分析法(ANP)和耦合逼近理想解排序法(TOPSIS)的煤矿风险预控管理体系有效性模型,从风险预控管理、保障管理、不安全行为管理、安全要素管理、综合管理和检查、审核与评审6个方面对煤矿风险预控管理体系有效性进行评估,最后以王楼煤矿为例进行实证研究。结果显示,计算参照值为0.51,说明该体系处于一般有效级别。其中该体系有效性的最大的影响因素是保障管理、不安全行为管理和安全要素管理3个方面,应加强对这3个方面的管理以提升其有效性。

基于云-TOPSIS法的应急物流供应商综合评价

为实现应急物流降本增效的目标,从供应商层面出发,运用云-逼近理想解排序法(TOPSIS)评价应急物流供应商综合能力;根据应急物流特点,从应急响应能力、物资质量、成本控制、应急响应柔性、企业内外部条件等5方面,构建应急物流供应商综合评价指标体系;借鉴博弈论思想,将用改进熵权法求得的客观权重和用层次分析法(AHP)求得的主观权重作为博弈对手,确定最优组合权重;运用云模型量化指标决策云和加权云对供应商的模糊定性评价语义;采用TOPSIS法构建正负理想解集合,计算备选方案与正负理想解的距离确定相对贴近度,确定最优备选方案。研究结果表明:指标决策云能准确地将评价语言量化,云-TOPSIS法的评价结果更合理;在供应商相对贴近度排序中,采用云-TOPSIS法计算的最优与最劣者差值为0.3315,而TOPSIS法为0.0882,两者相差0.2433,表明云-TOPSIS法的评价结果区分度更大,能更直观地辅助决策者做出最优选择。

基于TOPSIS法和波士顿矩阵的医院神经专科能力评估研究

目的通过对以神经科学集群建设为特色的三级甲等医院的神经专科能力进行评估,为国内医院的特色专科建设提供参考。方法从服务能力、技术能力、质量安全和服务效率4个维度建立神经外科、神经内科专科能力评估指标体系,通过优劣解距离(technique for order preference by similarity to ideal solution,TOPSIS)法纵向比较首都医科大学附属北京天坛医院神经专科2019—2023年发展趋势,并采用波士顿矩阵深入分析神经专科各亚专业建设情况。结果2019—2023年首都医科大学附属北京天坛医院神经专科TOPSIS综合得分指数呈上升趋势。神经外科以胶质瘤诊治为主的肿瘤专业1,在技术能力和质量安全方面得分指数最高;神经内科以脑血管病为主的亚专业,在技术能力和服务效率方面得分指数较高,以上两个亚专业在波士顿矩阵中均处于优势巩固区。结论2019—2023年首都医科大学附属北京天坛医院神经专科诊治能力不断提升。神经外科亚专业中,专科能力排名最高的为肿瘤专业1,诊疗技术难度较高,同时医疗质量负性事件发生率低。神经内科各亚专业中,脑血管专业诊疗技术难度高且服务高效。

一测多评法测定法制半夏曲中11种成分含量及其GRA、EW-TOPSIS质量评价

目的采用一测多评(QAMS)法同时测定法制半夏曲中肌苷、鸟苷、腺苷等11种成分含量,并建立其灰色关联度分析(GRA)联合熵权逼近理想解排序分析法(EW-TOPSIS)综合质量评价方法。方法采用Shimadzu C 18色谱柱;乙腈-0.5%醋酸为流动相,梯度洗脱,流速1.0 mL·min-1;检测波长254和290 nm。以对甲氧基肉桂酸乙酯为内参比物质,计算其他10个成分的相对校正因子(RCF),测定各成分含量。采用GRA联合EW-TOPSIS模型对法制半夏曲进行综合质量评价。结果法制半夏曲中11种成分在一定浓度范围内线性关系良好,相关系数均>0.999;平均加样回收率96.94%~100.12%(RSD<2.0%,n=9);QAMS与外标法(ESM)实测值无明显差异。GRA模型相对关联度0.2903~0.6187,EW-TOPSIS模型相对接近度0.2114~0.6343;GRA和EW-TOPSIS模型综合评价结果基本一致。结论QAMS法便捷、准确,可用于法制半夏曲多指标成分定量控制,GRA联合EW-TOPSIS模型可用于法制半夏曲综合质量评价。

基于DEMATEL-ANP-AEW-TOPSIS的配电网综合能效评估

根据中国配电网的发展特点和基本属性,在保证评估指标的科学性和可靠性的前提下,从电网运行、环境效益、分布式发电效益、经济效益、资源利用效率5个方面提出了适应于配电网综合能效评估的指标体系。针对目前配电网能效缺乏量化评估方法的问题,提出了新的配电网综合能效评价方法,即集DEMATEL、网络分析(analytic network process,ANP)法、反熵权(anti-entropy weight,AEW)法、逼近理想解排序法(technique for ordey preference by similarity to ideal solution,TOPSIS)于一体的主、客相结合的DEMATEL-ANP-AEWTOPSIS组合方法,并用该方法量化各个层次指标的权重以确定能效评估模型。实际算例结果验证了所提模型和方法可行、实用。

基于TOPSIS和GRA的信息安全风险评估

信息安全风险评估是一项非常重要的信息安全保障活动.依据信息安全相关标准,可从资产、威胁和脆弱性3方面识别出重要的风险因素,并确定相应的信息安全风险评估指标.参考等保2.0确定风险评估指标是一种可行的方法.在进行信息安全风险评估时,采用熵权法进行客观的指标赋权,并结合优劣解距离法(technique for order preference by similarity to ideal solution,TOPSIS)和灰色关联分析(grey relational analysis,GRA)进行综合评估.实例分析表明,依据信息熵进行客观赋权相对减少了主观因素的影响;基于TOPSIS和GRA进行信息安全风险评估,综合被评价对象整体因素和内部因素,较有效地将多项信息安全风险评估指标综合成单一评分,便于对多个被评对象进行信息安全风险的择优与排序.

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.

Combining TOPSIS and GRA for supplier selection problem with interval numbers

Supplier selection can be regarded as a typical multiple attribute decision-making problem. In real-world situation, the values of the alternative attributes and their weights are always being nondeterministic, and as a result of this, the values are considered interval numbers. In addition, the common approach to measure the similarity between alternatives through their distance suffers from some minor shortcomings. To address these problems, this study develops a novel hybrid decision-making method by combining the technique for order preference by similarity to an ideal solution （TOPSIS） with grey relational analysis （GRA） for supplier selection with interval numbers. By introducing the intervals theory, the extensions of Euclidean distance and grey relational grade are defined. And then a new comprehensive closeness coefficient is constituted for supplier alternatives evaluation based on the interval Euclidean distance and the interval grey relational grade, which could indicate the distance-based similarity and the shape-based similarity simultaneously. A mtmerical example is taken to validate the flexibility of the proposed method, and result shows that this method can tackle the uncertainty in real-world supplier selection and also help decision makers to effectively select optimal suppliers.

Weakness Ranking Method for Subsystems of Heavy-Duty Machine Tools Based on FMECA Information

Heavy-duty machine tools are composed of many subsystems with different functions,and their reliability is governed by the reliabilities of these subsystems.It is important to rank the weaknesses of subsystems and identify the weakest subsystem to optimize products and improve their reliabilities.However,traditional ranking methods based on failure mode effect and critical analysis(FMECA)does not consider the complex maintenance of products.Herein,a weakness ranking method for the subsystems of heavy-duty machine tools is proposed based on generalized FMECA information.In this method,eight reliability indexes,including maintainability and maintenance cost,are considered in the generalized FMECA information.Subsequently,the cognition best worst method is used to calculate the weight of each screened index,and the weaknesses of the subsystems are ranked using a technique for order preference by similarity to an ideal solution.Finally,based on the failure data collected from certain domestic heavy-duty horizontal lathes,the weakness ranking result of the subsystems is obtained to verify the effectiveness of the proposed method.An improved weakness ranking method that can comprehensively analyze and identify weak subsystems is proposed herein for designing and improving the reliability of complex electromechanical products.

Evaluation of Plant Landscape in Residential Areas Based on AHP and TOPSIS

Taking 6 residential areas in Nyingchi of Tibet as research objects,from aesthetic effect,ecological function and leisure service,this paper established the evaluation indicator system for plant landscape in residential areas using AHP,and calculated the weight of indicators using the judgment matrix. Besides,it calculated the ideal solution and closeness degree of matrix using TOPSIS,and established the evaluation method and preference method for plant landscape in residential areas. The results show that the indicators of seasonal variation,environmental benefit and per capita green space mattered most in the landscape evaluation of residential areas. The richness of flowering plant is weak in the landscape evaluation. From the comprehensive evaluation of residential areas,Nyingchi Garden District and Xingfu District have excellent plant landscape,Jialong Garden District and Shangcheng Garden District have general plant landscape,and Sun City District and Niyang Garden District have poor plant landscape.

基于AHP与TOPSIS的水电站能效管理水平评价方法研究

针对现有水电站能效管理水平评价方法的不足,将层次分析法(AHP)和优劣解距离法(TOPSIS)引入评价过程中,综合考虑经济、安全和管理3个方面的因素,构建了水电站能效管理评价指标体系;针对九分位标度法的不足,采用指数标度法确定各指标权重;分别利用TOPSIS方法和专家打分法对定量指标、定性指标进行评分,并进一步实现水电站能效管理水平的综合评价;以某实际水电站为例,分析和计算2018-2022年的水电站能效管理水平得分,结果表明该电站能效管理水平总体上呈上升趋势。

基于AHP和TOPSIS-模糊综合评价的多场景储能选型方法

目前储能技术路线多样,不同类型的储能各具应用前景,但储能选型需要综合考虑经济性、安全性等因素,是一个复杂的多目标决策问题,因此储能选型是工程应用中的关键问题之一。提出一种将层次分析法(analytic hierarchy process,AHP)和优劣解距离法(technique for order preference by similarity to ideal solution,TOPSIS)-模糊综合分析法相结合的储能选型评价体系。首先,通过建立评价体系的判断矩阵,利用AHP获取指标权重;其次,将判断矩阵里量纲不同的指标类型用TOPSIS做规范化处理,以此获得更客观的权重向量,改善AHP法的主观性;而后,将指标权重对角化处理并与标准化后的矩阵相乘获得加权判断矩阵,并求取贴近度向量。最后,加权判断矩阵与模糊综合分析法关系矩阵相乘获取储能类型的隶属度评价结果,并以隶属度最大值所在的等级为最终评价,处于等级Ⅰ中最佳,等级Ⅱ次之并以此类推;由此通过TOPSIS获得更客观的权重向量,改善AHP法的主观性,得到的权重向量也更客观。最后以锂离子电池、钠硫电池和铅酸电池等七种储能类型在应用于削峰填谷、电网保供电和改善电压质量场景为例,并与现有的储能选型方法进行比较,体现该评价体系的创新,检验所提评价体系和选型方法的有效性。

Optimal design of functionally graded Pm PV/CNT nanocomposite cylindrical tube for purpose of torque transmission

Carbon nanotube(CNT)/polymer nanocomposites have vast application in industry because of their light mass and high strength. In this work, a cylindrical tube which is made up of functionally graded(FG) PmP V/CNT nanocomposite, is optimally designed for the purpose of torque transmission. The main confining parameters of a rotating shaft in torque transmission process are mass of the shaft, critical speed of rotation and critical buckling torque. It is required to solve a multi-objective optimization problem(MOP) to consider these three targets simultaneously in the process of design. The three-objective optimization problem for this case is defined and solved using a hybrid method of FEM and modified non-dominated sorting genetic algorithm(NSGA-II), by coupling two softwares, MATLAB and ABAQUS. Optimization process provides a set of non-dominated optimal design vectors. Then, two methods, nearest to ideal point(NIP) and technique for ordering preferences by similarity to ideal solution(TOPSIS), are employed to choose trade-off optimum design vectors. Optimum parameters that are obtained from this work are compared with the results of previous studies for similar cylindrical tubes made from composite or a hybrid of aluminum and composite that more than 20% improvement is observed in all of the objective functions.

Fuzzy TOPSIS method to primary crusher selection for Golegohar Iron Mine(Iran)

Selection of the crusher required a great deal of design regarding to the mine planning. Selection of suitable primary crusher from all of available primary crushers is a multi-criterion decision making(MCDM) problem. The present work explores the use of technique for order performance by similarity to ideal solution(TOPSIS) with fuzzy set theory to select best primary crusher for Golegohar Iron Mine in Iran. Gyratory, double toggle jaw, single toggle jaw, high speed roll crusher, low speed sizer, impact crusher, hammer mill and feeder breaker crushers have been considered as alternatives. Also, the capacity, feed size, product size, rock compressive strength, abrasion index and application of primary crusher for mobile plants were considered as criteria for solution of this MCDM problem. To determine the order of the alternatives, closeness coefficient is defined by calculating the distances to the fuzzy positive ideal solution(FPIS) and fuzzy negative ideal solution(FNIS). Results of our work based on fuzzy TOPSIS method show that the gyratory is the best primary crusher for the studied mine.

Best compromising crashworthiness design of automotive S-rail using TOPSIS and modified NSGAⅡ

In order to reduce both the weight of vehicles and the damage of occupants in a crash event simultaneously, it is necessary to perform a multi-objective optimal design of the automotive energy absorbing components. Modified non-dominated sorting genetic algorithm II(NSGA II) was used for multi-objective optimization of automotive S-rail considering absorbed energy(E), peak crushing force(Fmax) and mass of the structure(W) as three conflicting objective functions. In the multi-objective optimization problem(MOP), E and Fmax are defined by polynomial models extracted using the software GEvo M based on train and test data obtained from numerical simulation of quasi-static crushing of the S-rail using ABAQUS. Finally, the nearest to ideal point(NIP)method and technique for ordering preferences by similarity to ideal solution(TOPSIS) method are used to find the some trade-off optimum design points from all non-dominated optimum design points represented by the Pareto fronts. Results represent that the optimum design point obtained from TOPSIS method exhibits better trade-off in comparison with that of optimum design point obtained from NIP method.