An integrated AHP and VIKOR for design concept evaluation based on rough number

Design concept evaluation at the early stage of product design has been widely recognized as one of the most critical phases in new product development as it determines the direction of the downstream design activities. However, the information at this stage is mainly subjective and imprecise which only depends on experts’ judgments. How to handle the vagueness and subjectivity in design concept evaluation becomes a critical issue. This paper presents a systematic evaluation method by integrating rough number based analytic hierarchy process (AHP) and rough number based compromise ranking method (also known as VIKOR) to evaluate design concepts under subjective environment. In this study, rough number is introduced to aggregate individual judgments and preferences and deal with the vagueness in decision-making. A novel AHP based on rough number is presented to determine the weight of each evaluation criterion. Then an improved rough number based VIKOR is proposed to evaluate the design concept alternatives. Sensitivity analysis is conducted to measure the impact of the decision makers’ risk to the final evaluation results. Finally, a practical example is put forward to validate the performance of the proposed method. The result shows that the proposed decision-making method can effectively enhance the objectivity in design concept evaluation under subjective environment.     

Integrated rough VIKOR for customer-involved design concept evaluation combining with customers’ preferences and designers’ perceptions

Customer-involved design concept evaluation (DCE) allows customers to take part in evaluating the design alternatives to get more popular design concept. Traditional customer-involved DCE methods still focus on the collection of customer responses and only consider cost and benefit characteristics of design criteria in multi-criteria decision-making (MCDM) based evaluation process. Few studies have customized the decision-making algorithms specifically aimed at customers’ preferences. This paper further explores the customers’ influences in the early stages of the product design development, and proposes a new rough number based MCDM model (i.e., VIKOR) incorporating customers’ preferences for design specifications along with designers’ perceptions for the characteristics of design criteria (cost and benefit) to perform concept evaluation under subjective environment, and this proposed method is named as integrated rough VIKOR (IR-VIKOR). The objective of this study is to identify the best design concept which maximizes the satisfactions of expectations from most customers as well as conforms to the characteristics of design criteria. Firstly, Shannon entropy is used to obtain the weightings and relative importance ratings of design criteria from the customers’ preferences. Secondly, the customers’ preferences for design attribute values, the importance ratings of design criteria and the characteristics of design criteria are combined together to define the ideal solutions to calculate the rough evaluation index of each design alternative in IR-VIKOR, and finally the ranking result is provided by IR-VIKOR to determine the best design concept. A practical design example is introduced to illustrate the evaluation process of this proposed method, and the empirical comparisons are further carried out to validate its superiority for DCE. Through the sensitivity analysis experiments including i) inside IR-VIKOR, and ii) between IR-VIKOR and other classical MCDM methods, the proposed method is proved to be a reliable and feasible customer-involved DCE approach.     

A new multi-criteria weighting and ranking model for group decision-making analysis based on interval-valued hesitant fuzzy sets to selection problems

The multi-criteria group decision-making methods under fuzzy environments are developed to cope with imprecise and uncertain information for solving the complex group decision-making problems. A team of some professional experts for the assessment is established to judge candidates or alternatives among the chosen evaluation criteria. In this paper, a novel multi-criteria weighting and ranking model is introduced with interval-valued hesitant fuzzy setting, namely IVHF-MCWR, based on the group decision analysis. The interval-valued hesitant fuzzy set theory is a powerful tool to deal with uncertainty by considering some interval-values for an alternative under a set regarding assessment factors. In procedure of the proposed IVHF-MCWR model, weights of criteria as well as experts are considered to decrease the errors. In this regard, optimal criteria’ weights are computed by utilizing an extended maximizing deviation method based on IVHF-Hamming distance measure. In addition, experts’ judgments are taken into account for computing the criteria’ weights. Also, experts’ weights are determined based on proposed new IVHF technique for order performance by similarity to ideal solution method. Then, a new IVHF-index based on Hamming distance measure is introduced to compute the relative closeness coefficient for ranking the candidates or alternatives. Finally, two application examples about the location and supplier selection problems are considered to indicate the capability of the proposed IVHF-MCWR model. In addition, comparative analysis is reported to compare the proposed model and three fuzzy decision methods from the recent literature. Comparing these approaches and computational results shows that the IVHF-MCWR model works properly under uncertain conditions.     

A data-driven decision support system for sustainable supplier evaluation in the Industry 5.0 era: A case study for medical equipment manufacturing

Effective supplier management is critical for an enterprise’s success, as supplier procurement accounts for up to approximately 70% to 80% of total manufacturing costs. Correct supplier selection can ensure the competitiveness of the enterprise and contribute to supply chain integration and innovation. In recent years, supplier evaluation frameworks based on Industry 4.0 concepts have contributed to the development of the industry. However, the novel concepts of Industry 5.0 require examination from a people-oriented and sustainable perspective. Unfortunately, at the present time, supplier evaluation frameworks based on Industry 5.0 are lacking. Therefore, the primary task of this study is to develop a novel and comprehensive supplier evaluation framework for the Industry 5.0 era. This study proposes a data-driven decision support system to execute the supplier evaluation process. First, variable precision- dominance-based rough set approach (VC-DRSA) is applied to extract the core criteria, to remove the noise factors and to generate decision rules for the decision-makers’ reference. Second, the criterion importance through intercriteria correlation (CRITIC) approach is adopted to obtain the dependency weights of the core criteria and their ranking. Finally, a modified classifiable technique for order preference by similarity to ideal solution (CTOPSIS) is used to integrate the final performance values of suppliers when new alternative suppliers are added. The research concept is in line with the conception of data-driven decision support in business intelligence and does not rely on the subjective judgments and opinions of experts. Data provided by a multinational medical equipment manufacturer are used as an example to demonstrate the proposed model. VC-DRSA retains nine core criteria from the original twenty criteria, which greatly reduces the labor and cost of supplier audits. In addition, the CRITIC results show that digital transformation, real-time information sharing, and organizational culture transformation are the three main factors affecting the development of enterprises towards Industry 5.0. The results show that CTOPSIS can be used to quickly assess the ratings of new alternative suppliers are listed.     

A group decision support approach to evaluating journals

One of the most important decisions made in academic institutions, research organizations, and government agencies is the grading or ranking of journals for their academic values. Current methods for evaluating journals use either a subjective (e.g., experts’ judgments on journals) or objective approach (e.g., impact factors of journals), or an informal mix of the two. This paper presents a formal procedure that integrates objective and subjective judgments to provide a comprehensive method. The procedure is based on a fuzzy set approach that deals with the imprecise and missing information inherent in the evaluation process. The system was tested in Hong Kong in an assessment of faculty research productivity. Similar assessments exist in the UK, Singapore, and other countries. The proposed model can also be used for similar decisions that involve subjective and objective information.     

A group decision support approach to evaluating journals

One of the most important decisions made in academic institutions, research organizations, and government agencies is the grading or ranking of journals for their academic values. Current methods for evaluating journals use either a subjective (e.g., experts’ judgments on journals) or objective approach (e.g., impact factors of journals), or an informal mix of the two. This paper presents a formal procedure that integrates objective and subjective judgments to provide a comprehensive method. The procedure is based on a fuzzy set approach that deals with the imprecise and missing information inherent in the evaluation process. The system was tested in Hong Kong in an assessment of faculty research productivity. Similar assessments exist in the UK, Singapore, and other countries. The proposed model can also be used for similar decisions that involve subjective and objective information.     

Quality attribute modeling and quality aware product configuration in software product lines

In software product line engineering, the customers mostly concentrate on the functionalities of the target product during product configuration. The quality attributes of a target product, such as security and performance, are often assessed until the final product is generated. However, it might be very costly to fix the problem if it is found that the generated product cannot satisfy the customers’ quality requirements. Although the quality of a generated product will be affected by all the life cycles of product development, feature-based product configuration is the first stage where the estimation or prediction of the quality attributes should be considered. As we know, the key issue of predicting the quality attributes for a product configured from feature models is to measure the interdependencies between functional features and quality attributes. The current existing approaches have several limitations on this issue, such as requiring real products for the measurement or involving domain experts’ efforts. To overcome these limitations, we propose a systematic approach of modeling quality attributes in feature models based on domain experts’ judgments using the analytic hierarchical process (AHP) and conducting quality aware product configuration based on the captured quality knowledge. Domain experts’ judgments are adapted to avoid generating the real products for quality evaluation, and AHP is used to reduce domain experts’ efforts involved in the judgments. A prototype tool is developed to implement the concepts of the proposed approach, and a formal evaluation is carried out based on a large-scale case study.     

基于专家主观信息的学术期刊评价方法研究

该文侧重于学术期刊定性属性的评价方法研究。学术期刊定性属性特征通常具有模糊性,因而往往需要由专家给出主观判断。通过建立基准语言等级评价集合,提出了将专家给出的关于各定性属性的主观评价信息规范化为基准语言等级评价集合并集成的综合评价方法。最后通过计算可以得到学术期刊的综合评价值,进而使得学术期刊评价尽可能的公平化。     

基于直觉模糊集和证据理论的群决策方法

针对属性值和权重均为直觉模糊数的多属性决策问题,提出一种基于直觉模糊集和证据理论的群决策方法.首先,对专家给出的每个方案的属性值和属性权重进行证据合成,在此基础上合成每个方案的所有属性值;然后,基于直觉模糊集相似度确定专家的相对权重,修正方案证据,并合成所有专家证据,得到方案的信任区间,根据信任区间的大小对方案进行排序;最后,通过数值案例验证了所提出方法的有效性和合理性.     

基于结构熵权 TOPSIS 法的产品设计方案评估研究

为了提高企业在产品设计方案评估阶段进行合理决策的效率,提出了一种基于结 构熵权双基点法(TOPSIS)的产品设计方案评估方法。在评估流程中,首先确定产品设计方案评 价指标,专家对各评价指标进行重要度排序,在得到了“典型排序”后经过结构熵计算和“认识盲 度”计算,得出各评价指标的权重,以替代双基点法中专家主观设定的权重系数;其次,构建设 计方案各指标加权标准决策的矩阵,进而求得各指标的理想解,基于以上可得到各设计方案距 离理想解的相对贴近度,经对比后确定设计方案的排序情况,从而得到各方案的优劣。最后, 将该评估流程应用于录音笔设计方案评估的决策中,验证了该方法的可行性与有效性。     

Design concept evaluation considering information reliability,uncertainty, and subjectivity: An integrated rough-Z-number-enhanced MCGDM methodology

Design concept evaluation plays a vital role in new product development due to its critical impact on successive design activities as well as the novelty and competence of the final product. Lots of decision-making techniques have been developed for the design concept evaluation under various contexts. However, existing methods mainly focus on the evaluation under precise environments or fuzzy set scenarios. Whereas in reality, most risk assessments are derived from experts’ subjective judgments. The reliability of the evaluation is rarely taken into consideration. To bridge this gap, this study proposes a rough-Z-number-enhanced MCGDM (multi-criteria group decision-making) to resolve the design concept evaluation considering information reliability, uncertainty, and subjectivity. A rough-Z-number is introduced to incorporate into the MCGDM framework to represent the individual evaluation and aggregate group risk assessments. A rough-Z-number-based AHP (analytic hierarchy process) is presented to determine the criteria weights. A rough-Z-number-based MABAC (multi-attributive border approximation area comparison) is proposed to rank the design concepts. Experiments and comparative analyses demonstrate the advantage of the rough-Z-number extended MCGDM in complex and uncertain decision-making environments. With the rough-Z-number-based enhancement, the information reliability, uncertainty, and subjectivity in design concept evaluation are well characterized.     

Fuzzy MCDM approach for selecting the best environment-watershed plan

In the real word, the decision-making problems are very vague and uncertain in a number of ways. Most of the criteria have interdependent and interactive features, so they cannot be evaluated by conventional measure method. Such as the feasibility, thus, to approximate the human subjective evaluation process, it would be more suitable to apply a fuzzy method in the environment-watershed plan topic. This paper describes the design of a fuzzy decision support system in multi-criteria analysis approach for selecting the best plan alternatives or strategies in environment watershed. The fuzzy analytic hierarchy process (FAHP) method is used to determine the preference weightings of criteria for decision makers by subjective perception (natural language). A questionnaire was used to find out from three related groups comprising 15 experts, including 5 from the university of expert scholars (include Water Resources Engineering and Conservation, Landscape and Recreation, Urban Planning, Environment Engineering, Architectural Engineering, etc.), 5 from the government departments, and 5 from industry. Subjectivity and vagueness analysis is dealt with the criteria and alternatives for selection process and simulation results by using fuzzy numbers with linguistic terms. It incorporated the decision-makers’ attitude towards the preference; overall performance value of each alternative can be obtained based on the concept of fuzzy multiple-criteria decision-making (FMCDM). This research also gives an example of evaluation consisting of five alternatives, solicited from an environment-watershed plan work in Taiwan, is illustrated to demonstrate the effectiveness and usefulness of the proposed approach. The result is useful for destination planning and the sustainability of watershed tourism resources as well.     

A hybrid comprehensive performance evaluation approach of cutter holder for tunnel boring machine

Cutter holder is a crucial component of tunnel boring machine (TBM), whose performance evaluation and selection needs to consider many factors, which is a challenging Multiple criteria decision-making (MCDM) problem. To enhance the TBM overall construction manifestation, it is fundamental to synthetically evaluate and accurately select the most suitable cutter holder from alternatives according to the engineering requirements and geological conditions. This paper develops a hybrid fuzzy comprehensive evaluation approach for cutter holder. In this approach, the weights of criteria are determined by Fuzzy Analytic Hierarchy Process (FAHP), and the max-min linear normalization is employed to integrate the information of qualitative and quantitative indicators of alternatives. Finally, the ranking and further comparison are achieved in the form of radar chart. A case study of cutter holder selection from six alternatives is carried out to validate the proposed approach. It shows that the proposed approach is effective, reasonable, complete and easy to operate, which can be promoted to the evaluation and selection of non-standard crucial components for large mechanical engineering equipment.     

Design a new mixed expert decision aiding system using fuzzy ELECTRE III method for vendor selection

Any decision process deals with two different concerns as its cornerstones, evaluating the alternatives and ranking them based on their performances. In any decision process, the former phase is usually the premise of the latter one. Alternatives’ evaluation is the concept that largely depends on the experts and their expertise, which increase uncertainty in the decision-making process. In addition to all proposed methods for having the experts’ knowledge as evaluations of the alternatives, utilizing expert decision support systems (EDSS) can be a sensible response to such a need. Having evaluated the alternatives in the first phase of a decision-making process, the second phase of the process deals with the ranking the alternatives based on their performances obtained from the first phase. In this paper, we discuss the architecture of a fuzzy system including both modules, utilizing fuzzy concept for dealing with the uncertainty of the problem. Concerning the problem we had been dealt with, our system comprises a fuzzy evaluation module, which is a fuzzy expert system and an appropriate tool for evaluating the existing alternatives promptly and smoothly, without the imposed time delays by the experts to propose their comments and the uncertainty of such expertise-based comments, and a fuzzy ranking module, which is a fuzzy version of ELECTRE III method ranking the alternatives based on their outranking relations and by considering the existing uncertainty in their performances. This way the final ranking is resulted from an independent fuzzy system, which has considered the existing uncertainty in the evaluations not once but twice. Our proposed system has been applied to a real case of vendor selection process in one of the greatest and the most famous companies in the Iranian oil industry, OIEC, and the results are discussed.     

Data transformation in the evidential reasoning-based decision making process

This paper describes the application of an evidential reasoning (ER)‐based decision making process to multiple‐criteria decision making (MCDM) problems having both quantitative and qualitative criteria. The ER approach is based on the decision theory and the theory of evidence and it uses the concept of ‘degree of belief’ to assess decision alternatives on each attribute. When faced with MCDM problems, evaluation and selection or ranking of alternatives appear to be both challenging and vital to arrive at a rational and robust decision. In the presence of both qualitative and quantitative evaluations in an MCDM problem, it is necessary, when using the ER‐based decision making process, to transform or convert quantitative data into a belief structure using a number of grades so that the converted belief structure and the original quantitative data are equivalent in values or utilities. This paper suggests three scenarios for data transformation and examines how the ranking of decision alternatives is changed when different scenarios of data transformation are used. Ranking of UK universities using the ER approach is illustrated as an example.     

Interval-valued intuitionistic fuzzy mathematical programming method for hybrid multi-criteria group decision making with interval-valued intuitionistic fuzzy truth degrees

As an important component of group decision making, the hybrid multi-criteria group decision making (MCGDM) is very complex and interesting in real applications. The purpose of this paper is to develop a novel interval-valued intuitionistic fuzzy (IVIF) mathematical programming method for hybrid MCGDM considering alternative comparisons with hesitancy degrees. The subjective preference relations between alternatives given by each decision maker (DM) are formulated as an IVIF set (IVIFS). The IVIFSs, intuitionistic fuzzy sets (IFSs), trapezoidal fuzzy numbers (TrFNs), linguistic variables, intervals and real numbers are used to represent the multiple types of criteria values. The information of criteria weights is incomplete. The IVIFS-type consistency and inconsistency indices are defined through considering the fuzzy positive and negative ideal solutions simultaneously. To determine the criteria weights, we construct a novel bi-objective IVIF mathematical programming of minimizing the inconsistency index and meanwhile maximizing the consistency index, which is solved by the technically developed linear goal programming approach. The individual ranking order of alternatives furnished by each DM is subsequently obtained according to the comprehensive relative closeness degrees of alternatives to the fuzzy positive ideal solution. The collective ranking order of alternatives is derived through establishing a new multi-objective assignment model. A real example of critical infrastructure evaluation is provided to demonstrate the applicability and effectiveness of this method.     

Developing a fuzzy TOPSIS approach based on subjective weights and objective weights

Multiple criteria decision making (MCDM) is widely used in ranking one or more alternatives from a set of available alternatives with respect to multiple criteria. Inspired by MCDM to systematically evaluate alternatives under various criteria, we propose a new fuzzy TOPSIS for evaluating alternatives by integrating using subjective and objective weights. Most MCDM approaches consider only decision maker’s subjective weights. However, the end-user attitude can be a key factor. We propose a novel approach that involves end-user into the whole decision making process. In this proposed approach, the subjective weights assigned by decision makers (DM) are normalized into a comparable scale. In addition, we also adopt end-user ratings as an objective weight based on Shannon’s entropy theory. A closeness coefficient is defined to determine the ranking order of alternatives by calculating the distances to both ideal and negative-ideal solutions. A case study is performed showing how the propose method can be used for a software outsourcing problem. With our method, we provide decision makers more information to make more subtle decisions.     

Toward developing agility evaluation of mass customization systems using 2-tuple linguistic computing

Mass customization (MC) relates to the ability to provide individually designed products and services to every customer through high process flexibility and integration. For responding to the mass customization trend it is necessary to develop an agility-based manufacturing system to catch on the traits involved in MC. An MC manufacturing agility evaluation approach based on concepts of TOPSIS is proposed through analyzing the agility of organization management, product design, processing manufacture, partnership formation capability and integration of information system. The 2-tuple fuzzy linguistic computing manner to transform the heterogeneous information assessed by multiple experts into an identical decision domain is inherent in the proposed method. It is expected to aggregate experts’ heterogeneous information, and offer sufficient and conclusive information for evaluating the agile manufacturing alternatives. And then a suitable agile system for implementing MC can be established.     

Affective judgment in creative design: A method of fitness evaluation to the problem/solution spaces

A method of fitness evaluation to the problem/solution spaces is proposed based on the affective judgment in creative design. Six experienced designers and one-hundred-one users participated in a set of exploratory experiments on affective judgement of automobile design. From the experimental data, we identify the differences in designer's affective appeal in a design and user's affective response to the design. From data analysis, we confirm the general validity of that the ‘creative’ aspect of design can be described by introducing the notions of ‘default’ and ‘surprise’ problem/solution spaces. The affective judgments based on the expectations of designers and users are shown to be an effective alternative to quantitative metrics in design evaluation and concept selection. The presented findings suggested that the success and creativity are not the same, the goal of design practice is to find solutions that are both creative and successful.     

Using linguistic preferences and grey relational analysis to evaluate the environmental knowledge management capacity

This study proposes a combined fuzzy grey relational analysis method based to deal with study objective. This study objective is aimed to present a perception approach to deal with supplier evaluation of environmental knowledge management capacities (EKMC) with uncertainty and lack of information. The ranking of best supplier might be a key strategic direction of other suppliers prior to EKMC. The solving procedure is as follows, (i) the weights of criteria and alternatives are described both in qualitative and quantitative information using fuzzy set theory; (ii) using a grey relational analysis to result the ranking order for all alternatives; (iii) an empirical study of supplier ranking problem in EKMC are used to resolve with this proposed approach and the result indicates that optimal supplier is with higher protection of the environmental knowledge from inappropriate or illegal use or theft (C7) and from the best alternative supplier to study its criteria ranking.