An Integrated Approach of Fuzzy Linguistic Preference Based AHP and Fuzzy COPRAS for Machine Tool Evaluation

Globalization of business and competitiveness in manufacturing has forced companies to improve their manufacturing facilities to respond to market requirements. Machine tool evaluation involves an essential decision using imprecise and vague information, and plays a major role to improve the productivity and flexibility in manufacturing. The aim of this study is to present an integrated approach for decision-making in machine tool selection. This paper is focused on the integration of a consistent fuzzy AHP (Analytic Hierarchy Process) and a fuzzy COmplex PRoportional ASsessment (COPRAS) for multi-attribute decision-making in selecting the most suitable machine tool. In this method, the fuzzy linguistic reference relation is integrated into AHP to handle the imprecise and vague information, and to simplify the data collection for the pair-wise comparison matrix of the AHP which determines the weights of attributes. The output of the fuzzy AHP is imported into the fuzzy COPRAS method for ranking alternatives through the closeness coefficient. Presentation of the proposed model application is provided by a numerical example based on the collection of data by questionnaire and from the literature. The results highlight the integration of the improved fuzzy AHP and the fuzzy COPRAS as a precise tool and provide effective multi-attribute decision-making for evaluating the machine tool in the uncertain environment.     

Effect of product recovery and sustainability enhancing indicators on the location selection of manufacturing facility

The inclusion of economical, environmental, and societal issues in all stages of doing business helps to bring about sustainable development. A business begins or expands by establishing new facilities, so selecting a facility location is a strategic and crucial decision. In the context of sustainability, the selection of location for different facilities can be a critical problem, especially for manufacturing firms that endorse the wide footprint of Extended Producer Responsibility policies. This study aims at prioritizing alternative potential locations for manufacturing firms with respect to the three dimensions of sustainability identified above. The three dimensions are assessed by factors obtained through a factor analysis and are grouped by corresponding invariable sub criteria. These sub criteria are chosen from the extant literature review. Then, the preferred order of alternative potential location is obtained by Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) based on each location's overall performance. The performance of each alternative potential location is assessed on the basis of overall weights of alternatives, evaluating factors, and triple bottom line attributes, which were obtained by Analytical Hierarchical Process (AHP). The multi criteria decision making technique, AHP, calculates the weights of the qualitative and quantitative criteria impacting the location selection problem. Then the approach of the study is validated by applying a case from real life; the results are justified by completing a sensitivity analysis on the relative importance weights of the three primary attributes (economical, environmental, and social). The results of the sensitivity analysis demonstrate an effective decision making technique for the optimal selection of sustainable manufacturing locations.     

Minimizing Environmental Risks Using Fuzzy TOPSIS: Location Selection for the ITU Faculty of Management

ABSTRACT

Environmental risk is a measure of potential threats to the environment and combines the probability that events will cause or lead to degradation of the environment and the severity of that degradation. Evaluation of environmental risk factors requires linguistic terms to be used rather than exact numerical assignments. The fuzzy set theory provides a useful tool for converting linguistic terms into numerical evaluations. In this article, we will try to select the best location for the Faculty of Management of the Istanbul Technical University taking care of the predetermined environmental criteria by using fuzzy TOPSIS. The decision matrix is composed of linguistic evaluations for the alternatives with respect to the environmental risk criteria. The Macka Campus area has been selected after the multicriteria evaluation. A sensitivity analysis is also realized to see if the minor changes in criteria weights cause any change in the ranking of alternatives. Unless the importance of the criteria rock or soil structure, remoteness to health facilities, transportation availability, and transportation costs is changed to be from low to extremely low importance, the Macka Campus is still the selected alternative.     

Risk-Based Evaluation of Turkish Agricultural Strategies using Fuzzy AHP and Fuzzy ANP

In this article, we propose a model for selection of an agricultural strategy for Turkey by using fuzzy analytical hierarchy process (AHP) and analytical network process (ANP) based on linguistic terms. Fuzzy AHP-based methodology will be discussed to tackle the different decision criteria such as risk factors, ecological structure, socioeconomic structure, and technological structure involved in the selection of an agricultural strategy for Turkey and ANP will represent an effective tool for providing a suitable solution for managers and government administrators of this case. The linguistic levels of comparisons produced by the experts for each comparison are tapped in the form of triangular fuzzy numbers in order to construct fuzzy pairwise comparison matrices. The implementation of the system is demonstrated by a problem having four stages of hierarchy that contains 4 criteria and 15 sub-criteria.     

Hierarchical Gene Selection and Genetic Fuzzy System for Cancer Microarray Data Classification

This paper introduces a novel approach to gene selection based on a substantial modification of analytic hierarchy process (AHP). The modified AHP systematically integrates outcomes of individual filter methods to select the most informative genes for microarray classification. Five individual ranking methods including t-test, entropy, receiver operating characteristic (ROC) curve, Wilcoxon and signal to noise ratio are employed to rank genes. These ranked genes are then considered as inputs for the modified AHP. Additionally, a method that uses fuzzy standard additive model (FSAM) for cancer classification based on genes selected by AHP is also proposed in this paper. Traditional FSAM learning is a hybrid process comprising unsupervised structure learning and supervised parameter tuning. Genetic algorithm (GA) is incorporated in-between unsupervised and supervised training to optimize the number of fuzzy rules. The integration of GA enables FSAM to deal with the high-dimensional-low-sample nature of microarray data and thus enhance the efficiency of the classification. Experiments are carried out on numerous microarray datasets. Results demonstrate the performance dominance of the AHP-based gene selection against the single ranking methods. Furthermore, the combination of AHP-FSAM shows a great accuracy in microarray data classification compared to various competing classifiers. The proposed approach therefore is useful for medical practitioners and clinicians as a decision support system that can be implemented in the real medical practice.     

Fuzzy evaluation of water quality classification

Traditional classification methods of the water quality parameters use crisp set, and the concentrations values which are close or far from the limits are considered in same classes. Moreover, usually, several parameters are considered in quality determination; therefore, differences of the classes of the parameters may be vagueness, especially, in public consideration.In this study, an index model for quality evaluation of surface water quality classification using fuzzy logic is proposed. In the method, traditional quality classes are transformed into continuous form and then the concentration values of the different quality parameters are summed using fuzzy rules, finally, defuzzyfication of this summed values develops the index. An application of this proposed index model for physical and inorganic chemical parameters in the Eber Lake water (in Turkey) are studied to demonstrate the practical application and feasibility of this index.     

Application of analytic hierarchy process in selecting a biological indicator for a river flow restoration

Biological indicators play a vital role in monitoring and assessing river health and their selections are, consequently, directly related to the overall success of monitoring programs. In this study, we employed the analytic hierarchy process (AHP) to select an appropriate indicator from several indicator candidates. The process was first to form a three level AHP model with four criteria and three indicator alternatives, and then to evaluate the indicator alternatives mathematically, and finally to obtain the most appropriate one with highest values. The use of the proposed model showed that it can be relatively easy to select the most desirable indicator from several candidates. Also, the selection process was performed mathematically which was somewhat transparent.     

基于GIS的四川省油橄榄生态适宜性模糊综合评价

综合考虑与油橄榄生活习性密切相关的气候、土壤、地形等因素,利用GIS分析方法对空间数据进行组织与计算,结合AHP方法确定各参评因子权重,并选择适当的隶属函数和模糊算子对四川省油橄榄生态适宜性进行模糊综合评判。结果表明:基于GIS的模糊综合评判方法所得出的评价结果与目前四川省油橄榄引种区的分布大体一致,较之传统的评价方法有着评价周期短、评价结果更加精细、更有利于小区域范围内生态适宜性的确定等优点。     

Multi-criteria evaluation of multi-purpose stand treatment programmes for Finnish boreal forests under changing climate

The aim of this study is determine the potential of multiple-criteria analysis (MCA) methodology to assess the utility of different multi-objective stand treatment programmes, in the boreal forest. Simulations over a planning period of 100 years under current and changing climate scenarios by a physiological growth model provided input data for the stochastic multi-criteria analysis of forest management alternatives. Expected utility with regard to a set of objectives was estimated with an additive utility model. Timber production, carbon sequestration and biodiversity were considered as partial objectives; these in term were represented by decision criteria. The weights of partial objectives and criteria were subjected to uncertainty due to missing exact stakeholder preference information. Generic probability distributions for individual weights were defined based on qualitative information. Alternative stand treatment programmes with regard to the decision criteria were evaluated by means of linear preference functions. In a Monte Carlo analysis the utility model was employed to evaluate eight stand treatment programmes for their performance regarding the management objectives. The effect of climate change on utility of stand treatment programmes was examined also as an important factor. Over two sites and three tree species just two out of eight stand treatment programmes analysed in this study were able to dominate the set of alternatives; namely the unthinned scenario and the highest increase in thinning thresholds scenario (UT(0, 0) and BT(+30, +30)) in which stocking was kept at higher level compared to the currently recommended guidelines for site and species. Reducing uncertainty in the utility model by assuming accurate weights for the decision criteria did not show large changes neither in expected utility nor in the ranking of alternatives. Ignoring necessary revisions of how the forest is to be managed in the future might potentially result in losses, not only for timber production but also for benefits such as carbon sequestration and other amenities including biodiversity.     

Fuzzy rule‐based decision support system for evaluation of long‐established forest restoration projects

Although the importance of monitoring and evaluation of restoration actions is increasingly acknowledged, availability of accurate, quantitative monitoring data is very rare for most restoration areas, particularly for long‐established restoration projects. We propose using fuzzy rule‐based expert systems to evaluate the degree of success of restoration actions when available information on project results and impacts largely relies on expert‐based qualitative assessments and rough estimates of quantitative values. These systems use fuzzy logic to manage the uncertainty present in the data and to integrate qualitative and quantitative information. To illustrate and demonstrate the potential of fuzzy rule‐based systems for restoration evaluation, we applied this approach to seven forest restoration projects implemented in Spain between 1897 and 1952, using information compiled in the REACTION database on Mediterranean forest restoration projects. The information available includes both quantitative and expert‐based qualitative data, and covers a wide variety of indicators grouped into technical, structural, functional, and socioeconomic criteria. The fuzzy rule‐based system translates expert knowledge of restoration specialists and forest managers into a set of simple logic rules that integrate information on individual indicators into more general evaluation criteria. The rule‐based approach proposed here can be readily applicable to any kind of restoration project, provided that some information, even if vague and uncertain, is available for a variety of assessment indicators. The evaluation of long‐established forest restoration projects implemented in Spain revealed important asymmetries in the degree of restoration success between technical, structural, functional, and socioeconomic criteria.     

On the Application of Fuzzy Decision Theory in Chemotherapy

1IntreductionTheliteratUreonmulti-Criteriondecisionmaking(MCDM)problemshas~tremendouslyintherecentpast.TwomajorareashaveevolvedwhiChbothconcentrateondecisionmakingwithseveralcriteria:multiobjectivedecisionmaking(MODM)andmulti-attributedecisionmaking(MADM).TheformerconcentratesoncontinuousdecisionspaceandthelatterfocusesonproblemswithdiscreteSPace.FuzzysettheoryhascontributedtoMODMproblemsaswellastheMADMProblems.ThegeneralMODMproblemcanbedeft.edLllasfollows:Twostagescangenerallybe…     

Fuzzy methods for assessing criteria and indicators of sustainable forest management

This paper describes the general concepts, meaning, and definitions of sustainability and proposes the use of soft methodologies, particularly fuzzy set theory, for its assessment. Criteria and indicators (C&I) are described as instruments to assess forest sustainability. Basic elements and concepts of fuzzy sets are described, including membership functions and their interpretations in the context of sustainable forest management. Moreover, fuzzy operators that can combine the operational concepts of sustainability, namely criteria and indicators are described. A simple illustrative example is described to demonstrate the application of these methodologies.     

Modified AHP-based decision-making model toward accurate selection of eligible maintenance media for production of <Emphasis Type="Italic">taxanes</Emphasis> in <Emphasis Type="Italic">Taxus baccata</Emphasis> callus culture

Attempts were made here to apply a modified analytic hierarchy process (AHP) approach based on refinement assay of dominated alternatives in monitoring the most reliable callus maintenance media (supplemented with l-glutamine and Casamino acid) of Taxus baccata callus cultures in terms of five criteria. Generally, regarding stem-derived calli, 6 out of 18 maintenance media were nominated as non-dominated alternatives, and following AHP ranking test Casamino acid-based media (i.e., A12, A15 and A19) were overall nominated as the premiere. Taking leaf-derived calli into account, only l-glutamine-based media in an ascending order of A8, A4, A6, A5, A9 and A3 were introduced as non-dominated alternatives. Such results connote that l-glutamine-based feeding appears to generate more significant results either for continuous calli growth or taxanes production. In contrast, regarding the second explant, stem, both amino acid supplies had fairly equal worth. Our findings, overall, demonstrate promising applications of the proposed AHP method regarding accurate selection of the best callus maintenance cultures of T. baccata for production of different taxanes including paclitaxel, Baccatin III and 10-deacetylbaccatin III. Similarly, this statistical approach could be also applicable for other crops, for instance, for accurate selection of the best callus cultures/media and consequently production improvement of a given plant secondary metabolite/product.     

Multi-actor multi-criteria sustainability assessment framework for energy and industrial systems in life cycle perspective under uncertainties. Part 1: weighting method

Purpose

Life cycle sustainability assessment is meaningful for the decision-makers/stakeholders to select the most sustainable option among multiple alternatives; however, there are usually various severe uncertainty problems in sustainability-oriented decision-making, i.e., the vagueness and ambiguity that existed in human judgments and the lack of information. This study aims at developing a novel life cycle multi-criteria sustainability assessment method for helping the decision-makers/stakeholders to determine the sustainability level of the industrial and energy systems. In part 1, an improved interval analytic hierarchy process (AHP) which allows multiple decision-makers/stakeholders to participate in the decision-making was developed to determine the weights of the criteria which were used in life cycle sustainability assessment.

Methods

It is usually difficult for the decision-makers/stakeholders to use the numbers from 1 to 9 and their reciprocals for determining the comparison matrix when using the traditional AHP method for weight calculation, because human judgments usually involve various uncertainties. In order to the overcome this weak point of the traditional AHP, an improved AHP, so-called interval AHP, in which, multiple decision-makers/stakeholders are allowed to participate in the decision-making and allowed to use interval numbers instead of crisp numbers to establish the comparison matrix for determining the weights of the criteria for life cycle sustainability assessment, has been developed.

Results and discussion

The proposed method was used to determine the weights of the four aspects for life cycle sustainability assessment including economic, safety, social, and environmental aspects. Five representative stakeholders were invited to participate in the decision-making. After Monte Carlo simulation, the final weights of the four aspects have been determined with the proposed interval AHP.

Conclusions and perspectives

An interval AHP method was developed for determining the weights of the criteria for life cycle sustainability assessment; the decision-makers are allowed to use interval numbers to establish the comparison matrix for weight calculation. The weighting coefficients determined by Monte Carlo method can accurately reflect the preferences and willingness of multi-actor comparing with the traditional AHP method. This paper merely presents a novel method to calculate the weights of the criteria for life cycle sustainability assessment, but the method for determining the sustainability performance has been presented in part 2.

     

Semi-Supervised Fuzzy Clustering with Feature Discrimination

Semi-supervised clustering algorithms are increasingly employed for discovering hidden structure in data with partially labelled patterns. In order to make the clustering approach useful and acceptable to users, the information provided must be simple, natural and limited in number. To improve recognition capability, we apply an effective feature enhancement procedure to the entire data-set to obtain a single set of features or weights by weighting and discriminating the information provided by the user. By taking pairwise constraints into account, we propose a semi-supervised fuzzy clustering algorithm with feature discrimination (SFFD) incorporating a fully adaptive distance function. Experiments on several standard benchmark data sets demonstrate the effectiveness of the proposed method.     

Selection Indices and Multivariate Analysis Show Similar Results in the Evaluation of Growth and Carcass Traits in Beef Cattle

This research evaluated a multivariate approach as an alternative tool for the purpose of selection regarding expected progeny differences (EPDs). Data were fitted using a multi-trait model and consisted of growth traits (birth weight and weights at 120, 210, 365 and 450 days of age) and carcass traits (longissimus muscle area (LMA), back-fat thickness (BF), and rump fat thickness (RF)), registered over 21 years in extensive breeding systems of Polled Nellore cattle in Brazil. Multivariate analyses were performed using standardized (zero mean and unit variance) EPDs. The k mean method revealed that the best fit of data occurred using three clusters (k = 3) (P < 0.001). Estimates of genetic correlation among growth and carcass traits and the estimates of heritability were moderate to high, suggesting that a correlated response approach is suitable for practical decision making. Estimates of correlation between selection indices and the multivariate index (LD1) were moderate to high, ranging from 0.48 to 0.97. This reveals that both types of indices give similar results and that the multivariate approach is reliable for the purpose of selection. The alternative tool seems very handy when economic weights are not available or in cases where more rapid identification of the best animals is desired. Interestingly, multivariate analysis allowed forecasting information based on the relationships among breeding values (EPDs). Also, it enabled fine discrimination, rapid data summarization after genetic evaluation, and permitted accounting for maternal ability and the genetic direct potential of the animals. In addition, we recommend the use of longissimus muscle area and subcutaneous fat thickness as selection criteria, to allow estimation of breeding values before the first mating season in order to accelerate the response to individual selection.     

基于人水关系的京津冀城市群水资源安全格局评价

京津冀城市群是我国乃至全世界人类活动对水循环扰动强度最大的地区之一,水资源过度开发利用不仅严重影响生态环境安全,而且制约着经济社会的可持续发展。基于人水关系协调视角,从水资源本底条件、水资源开发利用程度、水资源开发利用效率等3个方面建立了水资源安全综合评价指标体系,并根据国内外发展经验和相关标准确定了评价标准阈值,使得评价结果在不同的时空尺度上均具有可比性。然后通过熵技术支持下的层次分析法和多目标模糊隶属度函数,对2000—2014年京津冀城市群水资源安全的时空格局进行了定量评价。结果表明:(1)整个京津冀城市群的水资源安全指数多在0.2—0.4之间,属于不安全类型,但总体向临界安全类型转变;(2)各城市的水资源安全指数在时空尺度上表现出较大差异,总体表现为南低北高且随着时间的推移普遍提高的格局;(3)整个京津冀城市群及各城市水资源安全指数的次级指标在时空尺度上也表现出一定的差异性和地域一致性,它们交互作用,最终综合决定着水资源安全指数的时空变化。     

Allocating resources for cancer control--resolving multicriteria decision-making using the analytic hierarchy process

When competing programs ought to be financed simultaneously for the same purpose, an allocation problem occurs due to scarce resources, and different perspectives and preferences. Facing the problem needs determining criteria which the decision might be based on. Those criteria form the objectives (the scope) of the different participants, and are relevant for the achievement of the goal, providing a comprehensive resource allocation that bridges and integrates the different perspectives. In case of cancer control primary prevention, secondary prevention, therapy and tertiary prevention, education, basic sciences, and clinical trials form the alternatives. An analytic hierarchy process (AHP) is used for supporting decision-making in the resource allocation problem. AHP is a method for setting priorities, but can only work out the implications of what was declared through the pairwise-ranking process, namely the relative preferences, weighing the criteria and rating the alternatives two by two. In the first analysis the relative weights to criteria were 0.099 for 'distributive justice'; 0.120 for constitutional and human rights; 0.251 for lay opinion; 0.393 for EBM; 0.137 for cost-effectiveness. Ranking the alternatives using 'judgements' resulted in relative preference of 0.238 for therapy, 0.204 for primary prevention, 0.201 for secondary prevention, 0.135 for clinical trials, 0.111 for tertiary prevention, 0.066 for basic sciences and 0.045 for education. In the second analysis the relative importance of "cost-effectiveness" was doubled, thus resulting in 0.234 for therapy, 0.216 for secondary prevention, 0.183 for primary prevention, 0.145 for clinical trials, 0.113 for tertiary prevention, 0.063 for basic sciences and 0.046 for education. Sensitivity analysis has shown that increasing the relative weight of cost-effectiveness up to approximately 0.4 changes the rank of alternatives, and above 0.4 this criterion gives secondary prevention preferences. According to the relative rates computed in both of the models all criteria vote for therapy, but these preferences change at the high level of weights, in case of EBM, 'rights', and cost-effectiveness. Cost-effectiveness prefers secondary prevention to therapy; the criterion of constitutional and human rights and the criterion of evidence-based medicine vote for primary prevention.     

基于RS和GIS的珠江三角洲生态环境脆弱性综合评价

使用空间主成分分析法构建评价指标体系,采用层次分析法确定指标权重,结合遥感数据和地理信息系统软件,对珠江三角洲2004-2008年生态环境脆弱性进行了综合评价并对脆弱性成因进行分析.结果表明:生态环境极度和重度脆弱区主要分布在珠江三角洲中部,占整个研究区面积的34.0％;生态环境中度脆弱区主要分布在珠江三角洲东部,占25.5％;生态环境轻度和微度脆弱区主要分布在珠江三角洲西部,分别占28.7％和l1.8％.中度和轻度脆弱区占整个研究区面积的54.2％,表明珠江三角洲大部分区域的生态环境属中度和轻度脆弱.影响珠江三角洲生态环境脆弱性的自然因素主要有海拔高度、大暴雨日数、水土流失比率、易涝耕地面积比率、归一化植被指数、景观多样性指数,人为因素主要有人口密度、单位面积废水排放量、单位面积废气排放量、土地利用变化、化肥施用强度、农药使用强度、万人机动车拥有量、环保投资指数.极度和重度脆弱区的主要特征是海拔低、洪涝灾害发生频率高、易涝耕地面积多、植被破坏严重、污染强度大和环保投资指数小等.     

Use of the Analytic Hierarchy Process for Medication Decision-Making in Type 2 Diabetes

AimTo investigate the feasibility and utility of the Analytic Hierarchy Process (AHP) for medication decision-making in type 2 diabetes.MethodsWe conducted an AHP with nine diabetes experts using structured interviews to rank add-on therapies (to metformin) for type 2 diabetes. During the AHP, participants compared treatment alternatives relative to eight outcomes (hemoglobin A1c-lowering and seven potential harms) and the relative importance of the different outcomes. The AHP model and instrument were pre-tested and pilot-tested prior to use. Results were discussed and an evaluation of the AHP was conducted during a group session. We conducted the quantitative analysis using Expert Choice software with the ideal mode to determine the priority of treatment alternatives.ResultsParticipants judged exenatide to be the best add-on therapy followed by sitagliptin, sulfonylureas, and then pioglitazone. Maximizing benefit was judged 21% more important than minimizing harm. Minimizing severe hypoglycemia was judged to be the most important harm to avoid. Exenatide was the best overall alternative if the importance of minimizing harms was prioritized completely over maximizing benefits. Participants reported that the AHP improved transparency, consistency, and an understanding of others’ perspectives and agreed that the results reflected the views of the group.ConclusionsThe AHP is feasible and useful to make decisions about diabetes medications. Future studies which incorporate stakeholder preferences should evaluate other decision contexts, objectives, and treatments.