Distance-based fuzzy MCDM approach for evaluating flexible manufacturing system alternatives

Considering the high required capital outlay and moderate risk of a flexible manufacturing system (FMS) investment, economic justification techniques are insufficient by themselves since they cannot cope with the benefits such as flexibility and enhanced quality offered by advanced manufacturing technologies. A robust decision-making procedure for evaluating FMS requires the consideration of both economic and strategic investment measures. A distance-based fuzzy multicriteria decision-making (MCDM) framework based on the concepts of ideal and anti-ideal solutions is presented for the selection of an FMS from a set of mutually exclusive alternatives. The proposed method provides the means for integrating the economic figure of merit with the strategic performance variables. The multicriteria decision approach presented here enables us to incorporate data in the forms of linguistic variables, triangular fuzzy numbers and crisp numbers into the evaluation process of FMS alternatives. Linguistic variables are also used to indicate the criteria's importance weights assigned by the decisionmakers. A comprehensive example illustrates the application of the multicriteria decision analysis.     

Fuzzy analytic hierarchy process (FAHP) for multi-criteria selection of microalgae harvesting and drying processes

Microalgae are considered to be a promising source of biomass compared with first and second generation feedstocks. However, the high energy requirement for harvesting and drying of the algal biomass poses challenge to commercialization due to implications on both carbon footprint (CF) and cost. In this work, we propose a systematic methodology for the multi-criteria evaluation of alternatives for the harvesting and drying processes. A fuzzy analytic hierarchy process (FAHP) approach is used, where the pairwise comparison of the multiple criteria and alternatives were done to prioritize the best harvesting and drying method within the fuzzy bounds of the value judgment that satisfies the consistency index. FAHP also allows the degree of confidence of the expert to be quantified. A case study of four alternatives each for the harvesting and drying process is used to demonstrate the process. Technology capability, cost and environmental impacts (comprised CF, land footprint and water footprint) are identified as the selection criteria for harvesting and drying process, respectively. Results show that flotation is the best alternative for harvesting process, while sun drying is the best among the drying alternatives. Sensitivity analysis is used to give insights on the robustness of the decision model and enables the understanding of critical criteria that would significantly influence the ranking of the alternatives. The proposed FAHP approach therefore can effectively deal with the uncertainty of judgment in the decision-making process in the evaluation of microalgae harvesting and drying processes.     

Sustainable Supplier Selection Model in Supply Chains During the COVID-19 Pandemic

As global supply chains become more developed and complicated, supplier quality has become increasingly influential on the competitiveness of businesses during the Covid-19 pandemic. Consequently, supplier selection is an increasingly important process for any business around the globe. Choosing a supplier is a complex decision that can result in lower procurement costs and increased profits without increasing the cost or lowering the quality of the product. However, these decision-making problems can be complicated in cases with multiple potential suppliers. Vietnam's textile and garment industry, for example, has made rapid progress in recent years but is still facing great difficulties as the supply of raw materials and machinery depends heavily on foreign countries. Therefore, it is extremely important for textile and garment manufacturing companies in Vietnam to implement an effective supplier evaluation and selection process. While multicriteria decision-making models are frequently employed to assist with supplier evaluation and selection problems, few of these models consider the problem under the condition of a fuzzy decision-making environment. The aim of this paper is to create a hybrid MCDM model using the Fuzzy Analytical Hierarchy Process (FAHP) model and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to assist the supplier selection process in the garment industry in a fuzzy decision-making environment. In this study, the FAHP method is used to evaluate the performance and the weight of each criterion. TOPSIS is then used to rank all potential suppliers. The proposed model is then applied to a real-world case study to demonstrate both the process of calculation as well as its real-world applicability. The results from the case study provide empirical evidence that the model is feasible. The proposed approach can also be used in combination with other MCDM models to better support decision makers and can be modified to be applied in similar supplier selection processes for different industries.     

Group-based product scheme-screening decision method based on fuzzy AHP and evidential reasoning theory

Selecting the favourable product scheme is the first step to successful new product development (NPD). There are usually large numbers of uncertainties in product scheme evaluation and screening process of NPD due to lack of or incomplete reliable information. Considering fully the uncertainties and then conducting correct reasoning could guarantee reliability and rationality of scheme-screening results. As an extension of analytic hierarchy process (AHP), fuzzy AHP inherits multi-merits of the AHP approach and is capable of dealing with fuzzy information effectively, but it still has two weaknesses. One is the well-known ranking reversal problem. Although several researchers have analysed the reasons, we think the root cause for ranking reversal problem is due to the fact that AHP treats weights of attribute criteria and performance scores of alternatives in the same way. Therefore, we intend to deal with attribute weights and performance scores of alternatives separately and introduce evidential reasoning (ER) theory, which is good at uncertain reasoning, into fuzzy AHP to calculate the performance scores of alternatives. On the other hand, in view of the difficulty in resolution for fuzzy weights from fuzzy comparison matrix, a linear goal-programming model is proposed to calculate fuzzy weights, whose objective is to minimise the inconsistency degree of comparison matrix. By combining fuzzy AHP with ER, a group-based hybrid decision model FAHP-ER is developed. The hybrid model not only gets a great improvement in the capability of dealing with uncertainty, but also reflects the most real decision scenario and thinking process of the decision maker. Finally, a case study for schemes screening of the rotor and bearing system in the turbine generator is presented to demonstrate the application of the hybrid decision method.     

Hesitant fuzzy programming technique for multidimensional analysis of hesitant fuzzy preferences

The linear programming technique for multidimensional analysis of preferences (LINMAP) is the most representative method for handling the multiple criteria decision making (MCDM) problems with respect to the preference information over alternatives. This paper utilizes the main structure of LINMAP to develop a novel hesitant fuzzy mathematical programming technique to handle MCDM problems within the decision environment of hesitant fuzzy elements (HFEs). Considering the hesitancy of the decision maker, both the pair-wise comparison preference information over alternatives and the evaluation information of alternatives with criteria are represented by the HFEs. Based on the incomplete pair-wise preference judgments over alternatives, we propose the concepts of the hesitant fuzzy consistency and inconsistency indices. Furthermore, we construct a hesitant fuzzy mathematical programming model to derive the weights of criteria and the positive-ideal solution. In this hesitant fuzzy programming model both the objective function and partial constraints’ coefficients take the form of HFEs, and an effective approach based on the ranking method of HFEs is further developed to solve the new derived model. To address the incomplete and inconsistent preference structures of criteria weights, we introduce several deviation variables and establish the bi-objective nonlinear programming model. At length, we employ a green supplier selection problem to illustrate the feasibility and applicability of the proposed technique and conduct a comparison analysis to validate its effectiveness.     

结构选型中基于模糊推理的评判系统

本文在基于自组织竞争神经网络检索机制与模糊逻辑评判的实例推理系统基础上，讨论了该系统用于结构选型过程中的模糊推理过程；建立了高层建筑结构高度适应性的模糊评价标准；并将其应用于模糊推理系统中；以剪力墙结构高度适应性评价为例展示了推理过程。证明采用模糊推理系统作为设计型结构选型决策支持系统的评价模块是理想的解决方案。     

Maintenance policy selection in manufacturing firms using the fuzzy MCDM approach

In manufacturing firms, there is a critical need for proper maintenance of manufacturing facilities. The maintenance process enhances customer satisfaction and reliability of the products, and increases the profit of the manufacturer. Therefore, a proper maintenance policy selection is a critical issue for manufacturers, as an inefficient maintenance policy affects not only the direct cost of the firm but also the other aspects. In the present study, maintenance policy selection at the level of the firm rather than the equipment level is shown, and for selection various criteria have been identified. The presented work not only provides the best alternatives but also provides an alternative ranking, which facilitates decision-makers in choosing alternatives according to their constraints. These selection criteria are different in nature, as some give a crisp value, whereas others are defined in linguistic terms. To select the appropriate maintenance policy, a distance-based fuzzy multicriteria decision-making (MCDM) approach has been employed. The proposed method provides the means for integrating the economic figure of merit with the strategic performance variables. The MCDM approach is efficient in incorporating data, in the form of linguistic variables, triangular fuzzy numbers, and crisp numbers, into the evaluation process of maintenance policy alternatives. A comprehensive example illustrates the application of the distance-based fuzzy MCDM approach.     

Decision-oriented Usability Evaluation of an Operation Interface: Model and Application

To support multifactor decision problems about usability evaluation,especially when studies fall short of comparable objects,a fuzzy synthetic evaluation model is explored in this paper. Grey relational analysis ( GRA) is brought in the model to calculate weight vectors of the usability factors. And membership functions of a remark vector are constructed in the context of use of the operation interface. The present method is applied in usability evaluation of operation interface and is proved to be effective. The comprehensive usability gradation of the operation interface to good is 0.6164 that meets the requirements in practice.     

A fuzzy AHP-based simulation approach to concept evaluation in a NPD environment

The evaluation process of conceptual design alternatives in a new product development environment is a critical point for companies who operate in fast-growing markets. Various methods exist that are able to successfully carry out this difficult and time-consuming process. One of these methods, the Analytic Hierarchy Process (AHP) has been widely used to solve multiple-criteria decision-making problems (i.e., concept evaluation, equipment selection) in both academic research and in industrial practice. However, due to vagueness and uncertainty in the decision-maker's judgment, a crisp, pair-wise comparison with a conventional AHP may be unable to accurately capture the decision-maker's judgment. Therefore, fuzzy logic is introduced into the pair-wise comparison in the AHP to compensate for this deficiency in the conventional AHP. This is referred to as fuzzy AHP. In this paper, a fuzzy AHP method is used to reduce a set of conceptual design alternatives by eliminating those whose scores (or weights) are smaller than a predetermined constant value obtained under certain circumstances. Then, simulation analysis is integrated with the fuzzy AHP method, and the hybrid method is used to help the decision-makers (product engineers or managers) evaluate the remaining alternatives from the fuzzy AHP method. A real-life manufacturing system is used as the testbed for the proposed techniques. Finally, the results of both techniques, fuzzy AHP and simulation, are used for Preference Ratio analysis to reach to the final alternative.     

基于物元分析与云模型的地下工程围岩稳定性评价

针对以往地下工程岩体质量评判过程中存在的模糊性与随机性问题,根据岩石质量指标、岩石单轴饱和抗压强度、岩体完整性系数、结构面强度系数和地下渗水量这5项指标建立地下工程围岩稳定性评价指标体系.基于物元分析法,通过计算专家评判矩阵的效度物元及合成权重物元来确定评价指标的重要性.根据确定的评价标准,得到各评价因子隶属于各级别的综合云模型,并针对广州抽水蓄能电站二期地下工程岩体实测数据,先通过正向云发生器计算各评价因子所对应的各个评价级别的隶属度,再与其权重结合得到合成隶属度,然后以最大隶属度为依据判别出岩体稳定性所属级别.将该方法所得评价结果与约简概念格-模糊优选评判法、粗糙集-逼近理想解的排序法(RS-TOPSIS)进行对比,三者判别等级一致,表明该方法准确可靠,且免除了对大量样本的学习过程,能够克服评价指标定性语言和定量数值相互转换所产生的模糊随机性,可以用于地下工程岩体稳定性的评判.     

FESOLE-fuzzy expert system for determining the optimal level of enforcement

Electronic payment for using road infrastructure is an area that is gaining importance in the realm of intelligent transportation systems (ITS). While preparing such an electronic fee collection system, the level of enforcement needed must be determined. This is not a trivial task, because it is affected by many technical and monetary factors. At the same time, it cannot be expected that all decision makers are deeply involved in this field and are able to make an optimal decision depending on the recommendations of external experts. In order to decrease the possibility of manipulating this decision process by lobbyists and to save the money used for external consultants, a decision support system is needed. This paper describes a fuzzy expert system for determining the optimal level of enforcement ? FESOLE. It bridges a missing part in the research concerning ITS. The author focuses mainly on the major technical features of this model. A fuzzy expert system is used to approach this problem. It can extract and exploit the knowledge of human experts and convert it to a robust computational model. Suitability of this methodology for a given task is also demonstrated.     

基于模糊群决策的天津特色食品包装SPA–TOPSIS评价

目的 针对地方特色食品包装设计需兼具功能性和文化性的特征,开展包装设计方案评价,有效辅助设计开发过程,丰富地方特色食品包装设计的思路。方法 以天津特色食品——麻花包装为研究对象,构建分层次的包装评价准则框架;采用基于梯形模糊数的专家评价法来获得备选方案在各准则上的评分,通过群决策来集结多位专家的评判意见,进而求解得到备选方案的准则值;引入集对分析理论(SPA),采用连接向量距离来替换经典TOPSIS中的欧氏距离,提出SPA–TOPSIS评价方法来实现备选方案的评价和排序。结果 针对麻花的6种包装设计方案,实施了基于模糊群决策的SPA–TOPSIS评价,6种包装设计方案与正理想解的贴近度依次为0.55、0.46、0.53、0.49、0.56、0.44,方案5为最优方案。结论 通过天津特色食品包装评价,完善了城市文化内涵包装设计的理念,为包装的文化性设计提供了重要支持。     

Selecting suppliers using a new fuzzy multiple criteria decision model: the fuzzy balancing and ranking method

In this paper, we present a fuzzy multiple criteria decision making (FMCDM) model known as fuzzy balancing and ranking. In contrast to other MCDM models, our proposed model does not require the weights of decision making criteria. First, we appraise the performance of alternatives against criteria via linguistic variables which are expressed as triangular fuzzy numbers. The foregoing model obtains the alternative rankings through a four-stage process. Second, an outranking matrix is derived indicating that the frequency with which one alternative is superior to all other alternatives based on each criterion. Third, the outranking matrix is triangularised to obtain an implicit pre-ordering or provisional order of alternatives. Fourth, the provisional order of alternatives is subjected to various screening and balancing operations that require sequential application of a balancing principle to the so-called advantages–disadvantages table that combines the criteria with the pair-wise comparisons of alternatives. Additionally, to demonstrate the procedural implementation of the proposed model and its effectiveness, we apply it on a case study regarding the problem of supplier selection.     

Provident decision making by considering dynamic and fuzzy environment for FMS evaluation

When evaluating complexity, cost and risk increase, it is difficult to make a proper decision. In such situations it is necessary to develop a model which simulates a decision maker's mind and consider both a dynamic and a fuzzy environment. In this study future oriented indices are presented which enable us to consider the effect of future changes in the index value during the decision making process. These future oriented indices are named provident indices. Also in this study to effectively integrate these multiple criteria into the decision making process, based on the analysis of the decision situation in such assessments, a suitable concept is selected. This method is based on the preference ranking organisation method for enrichment evaluations (PROMETHEE) which brings together flexibility and simplicity for the user and is therefore chosen for the enhancement towards the evaluation of fuzzy data on preferences, scores and weights. The model developed to investigate these impacts cannot perfectly reproduce all the events of the real system, but it can consider a fair number of elements of variability, which should be identified and analysed by considering present conditions and prediction about criteria values in future periods. Such a model may provide solutions with a high degree of robustness and reliability, comparable with those obtained by direct experimentation, but with a low computational cost. The uniqueness of this paper lies in two important areas: first, the incorporation of variability fuzzy and provident measures in the performance of alternatives into the decision making process; and second, is in the application of fuzzy PROMETHEE that provides the decision maker with effective alternative choices by identifying significant differences among alternatives and appropriate choices through considered future periods, and presents graphic aids for better interpretation of results. A comprehensive numerical example of a flexible manufacturing system (FMS) is provided to illustrate the results of the analysis. In a real-world manufacturing environment, the dynamics of an FMS and its stochastic characteristics require a specific approach for evaluation. This paper specifically focuses on FMSs due to the complexities involved in their proper evaluation that include factors such as high operational and managerial expertise in system implementation phases, high costs and risks. Due to these, evaluation, justification, and implementation of an FMS have been areas of major concern and importance for practitioners and researchers. In this case, various strategic, economic and operational criteria that envelop quantitative, qualitative, tangible, and intangible factors are considered.     

The human error rate assessment and optimizing system HEROS — a new procedure for evaluating and optimizing the man–machine interface in PSA

A new procedure allowing the probabilistic evaluation and optimization of the man–machine system is presented. This procedure and the resulting expert system HEROS, which is an acronym for Human Error Rate Assessment and Optimizing System, is based on the fuzzy set theory. Most of the well-known procedures employed for the probabilistic evaluation of human factors involve the use of vague linguistic statements on performance shaping factors to select and to modify basic human error probabilities from the associated databases. This implies a large portion of subjectivity. Vague statements are expressed here in terms of fuzzy numbers or intervals which allow mathematical operations to be performed on them. A model of the man–machine system is the basis of the procedure. A fuzzy rule-based expert system was derived from ergonomic and psychological studies. Hence, it does not rely on a database, whose transferability to situations different from its origin is questionable. In this way, subjective elements are eliminated to a large extent. HEROS facilitates the importance analysis for the evaluation of human factors, which is necessary for optimizing the man–machine system. HEROS is applied to the analysis of a simple diagnosis of task of the operating personnel in a nuclear power plant.     

模糊理想解法在多准则群决策中的应用

将模糊数学理论引入到不确定环境下的多准则群决策问题中,利用模糊理想解法进行方案排序.用三角模糊数来描述模糊准则权重和模糊准则属性值,给出了使用模糊理想解法进行群决策问题求解的一般步骤;通过供应商选择这一实例验证了本方法的有效性.     

基于改进模糊算法的污水源热泵系统运行能效评价

针对传统的模糊评价方法存在多因素耦合和专家打分不一致的问题,提出了一种改进的模糊评价方法以提高评价指标权重计算的准确性。将层次分析法、三标度法和拟优一致判断矩阵结合改进模糊评价模型,免去了一致性检验这一环节,以沈阳沈抚新区一处综合建筑为例,构建污水源热泵系统运行能效评价指标体系,结果表明,一级指标的排序分别为经济效益,权重0.501,环境效益指标,权重0.303,社会效益指标最低。二级指标中,热源效率权值最高为0.217,是影响目标集中供热系统运行能效的最主要因素,优化热源配置可以更好地挖掘节能潜力,其次应适当增大系统运行时热水供回水温差。     

Effects and relationships of parameters in a rule–based fuzzy system

Hierarchies of criteria and fuzzy rule systems represent an approach which effectively portrays the problem of multiple objectives found in classic decision–making scenarios such as order sequencing or the evaluation of various corporate strategies. They further help the decision–maker to select a concrete course of action. The relevant decision criteria are formalized with the help of linguistic variables. A hierarchy of criteria is then used to relate them to one another and to combine them by rule–bases. Evaluation using fuzzy sets leads to an aggregated rating of the individual alternatives. A problem of such fuzzy systems is the large number of required parameters and their influence on the evaluation results. This article will use the example of a simple criteria hierarchy for a sequencing problem to analyze the effects of individual parameters and their relationships amongst one another in a fuzzy system.     

An integrated fuzzy multi-criteria group decision-making approach for green supplier evaluation

Purchasing is one of the most vital functions within a company and supplier performance evaluation is one of the most important business processes of the purchasing function. Traditionally, companies have considered factors such as price, quality, flexibility, etc. while evaluating suppliers. However, environmental pressures urge them to consider green issues. This study proposes a decision model for supplier performance evaluation by considering various environmental performance criteria. An integrated, fuzzy group decision-making approach is adopted to evaluate green supplier alternatives. More precisely, a fuzzy analytic hierarchy process (AHP) is applied to determine the relative weights of the evaluation criteria and an axiomatic design (AD)-based fuzzy group decision-making approach is applied to rank the green suppliers. Finally, a case study is given to demonstrate the potential of the methodology.     

Using FANP approach on selection of competitive priorities based on cleaner production implementation: a case study in PCB manufacturer,Taiwan

The aim of this paper is to identify and discuss some of the important and critical decision criteria including cleaner production implementation of an efficient system to prioritize competitive priorities. Fuzzy analytic network process (FANP) based methodology is discussed to tackle the different decision criteria involved in the selection of competitive priorities in current business scenario. FANP is an efficient tool to handle the fuzziness of the data involved in deciding the preferences of different decision variables. The linguistic level of comparisons produced by the professionals and experts for each comparison are tapped in the form of triangular fuzzy numbers to construct fuzzy pairwise comparison matrices. The implementation of the system is demonstrated by a problem having four stages of hierarchy which contains different criteria, attributes and alternatives at wider perspective. The proposed model can provide a hierarchical framework for the cleaner production implemented organization to select on its competitive priorities.