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In the literature, many multi attributes decision making (MADM) models allow evaluation of the alternatives considering their current or last performance. However, in some MADM problems, not only current performance of alternatives but also their past performance should be taken into account in order to select the most appropriate alternative. For this reason, the purpose of this paper is to develop four procedures to evaluate the alternatives in MADM problems with multi terms.

This study uses dynamic operators to aggregate the evaluation in different terms and then, grey relational analysis (GRA) and technique for order preference by similarity to ideal solution (TOPSIS) methods are utilized to determine the most appropriate alternative. Thus, four procedures which consist of these operators and methods are developed to evaluate the alternatives in multi terms.

Some numerical examples are presented for the proposed procedures in multi-terms. Moreover, these four procedures are compared with other four procedures. The analyses of the results show that dynamic aggregation operators based on intuitionistic fuzzy set (IFS) and interval valued intuitionistic fuzzy sets (IVIFS) with GRA and TOPSIS can be used jointly for MADM problems in which alternatives are evaluated for different terms.

One of the significant mistakes faced in some MADM problems is to take into account the current performance of alternatives or is to ignore their past performance. The right selection depends on past and current performance of the alternatives. The novelty of this study is to propose four procedures for solving MADM problems in multi terms based on IFS and IVIFS using dynamic aggregation operators and GRA and TOPSIS methods.

The purpose of this paper is to develop some picture uncertain linguistic aggregation operators based on Bonferroni mean operators, which is combined with multiple attribute decision-making (MADM) and has applied the proposed MADM model for selecting the service outsourcing provider of communications industry under picture uncertain linguistic environment.

The service outsourcing provider selection problem of communications industry can be regarded as a typical MADM problem, in which the decision information should be aggregated. In this paper, the authors investigate the MADM problems with picture uncertain linguistic information based on traditional Bonferroni mean operator.

The results show that the proposed model can solve the MADM problems within the context of picture uncertain linguistic information, in which the attributes are existing interaction phenomenon. Some picture uncertain aggregation operators based on Bonferroni mean have been developed. A case study of service outsourcing provider selection problem of communications industry is provided to illustrate the effectiveness and feasibility of the proposed methods. The results show that the proposed methods are useful to aggregate the picture uncertain linguistic decision information in which the attributes are not independent so as to select the most suitable supplier.

The proposed methods can solve the picture uncertain linguistic MADM problem, in which the interactions exist among the attributes. Therefore, it can be used to solve service outsourcing provider selection problems and other similar management decision problems.

This paper develops some picture uncertain aggregation operators based on Bonferroni mean and further presents two methods based on the proposed operators for solving MADM problems. It is useful to deal with multiple attribute interaction decision-making problems and suitable to solve a variety of management decision-making applications.

It is useful to deal with multiple attribute interaction decision-making problems and suitable to solve a variety of management decision-making applications.

The paper investigates the MADM problems with picture uncertain linguistic information based on traditional Bonferroni mean operator and develops the picture uncertain linguistic Bonferroni mean operator and picture uncertain linguistic geometric Bonferroni mean operator, picture uncertain linguistic weighted Bonferroni mean operator and picture uncertain linguistic weighted geometric Bonferroni mean operator for aggregating the picture uncertain linguistic information, respectively. Finally, a numerical example concerning the service outsourcing provider selection problem of communications industry is provided to illustrate the effectiveness and feasibility of the proposed methods.

Multiple attribute decision making (MADM) is a conceptual agenda used for evaluation and selection of optimal nanofluid to assure best performance of heat exchanger. Most of the studies focus on nanofluids focus on individual ability at one time. Relatively, not even a single study is available for selection of nanofluid for heat exchanger using concurrent design and MADM approach. The purpose of this paper is to propose a concurrent design methodology using MADM approach to assist improved design of heat exchanger concurrently for all the x-abilities in an integrated manner.

A combined methodology of applying MADM approach using concurrent design for x-abilities is called CE-MADM approach. Implementation of nanofluid to improve thermal performance of heat exchanger entails thorough evaluation of nanofluids in various x-abilities (performance, maintenance, thermophysical properties and modelisation) to make exhaustive management decision. Sensitivity analysis is also proposed to study the behaviour of height of variation of density, heat capacity, thermal expansion and thermal conductivity with varying particle volume fraction and variation of relative closeness of available alternates from ideally best possible solution.

MADM approach considering various x-abilities concurrently provide an approach for relative ranking of available nanofluids for optimum performance. Fishbone diagrams of all x-abilities are constructed to identify all the attributes and converge large number of attributes into single numerical index that are concurrently responsible for the cause thus saving time for easy evaluation, comparison and ranking by decision makers. Sensitivity analysis to demonstration height of variation of pertinent attributes with varying particle volume fraction. A MATLAB programming is established to execute calculations involved in the procedure.

This paper comprises a predictable and effective mathematical approach to improve design of heat exchanger with nanofluid bearing in mind all the required x-abilities concurrently. This combined approach of CE-MADM is never applied before in the field of nanofluid to predict best possible results in feasible conditions considering all the x-abilities. Sensitivity analysis is also presented from the assumed mathematical equations of thermophysical properties.

The purpose of this paper is to develop a method for solving the multiple attribute decision-making (MADM) problem in which the decision maker can provide the five types of attribute aspirations, namely: benefit type with requirements; cost type with requirements; interval type; benefit type; and cost type.

First, for each type of attribute aspiration, the calculation formula of utility values of alternative concerning attributes is given. Then, using the calculation formulae, the attribute values are transformed into the corresponding utility values. On the basis of this, the overall ranking value of each alternative is calculated. Further, a ranking order of alternatives can be determined according to the obtained overall ranking values.

Research shows that it is necessary to develop the method for MADM with attribute aspirations. The example shows that the proposed method is applicable.

The proposed method can be applied to the selection of wastewater treatment technologies or other areas.

This paper proposes a new MADM method with multiple types of attribute aspirations. It develops and enriches the existing MADM methods.

The purpose of this paper is to study a novel grey possibility degree approach, which is combined with multi-attribute decision making (MADM) and applied MADM model for solving supplier selection problem under uncertainty information.

The supplier selection problem is a typical MADM problem, in which information of a series of indexes should be aggregated. However, it is relatively easy for decision makers to define information in uncertainty, sometimes as a grey number, rather than a precise number. By transforming linguistic scale of rating supplier selection attributes into interval grey numbers, a novel grey MADM method is developed. Steps of proposed model were provided, and a novel grey possibility degree approach was proposed. Finally, a numerical example of supplier selection is utilized to demonstrate the proposed approach.

The results show that the proposed approach could solve the uncertainty decision-making problem. A numerical example of supplier selection is utilized to demonstrate the proposed approach. The results show that the proposed method is useful to aggregate decision makers’ information so as to select the potential supplier.

The approach constructed in the paper can be used to solving uncertainty decision-making problems that the certain value of the decision information could not collect while the interval value set could be defined. Obviously it can be utilized for other MADM problem.

The paper succeeded in redefining interval grey number, constructing a novel interval grey number based MADM approach and providing the solution of the proposed approach. It is very useful to solving system forecasting problem and it contributed undoubtedly to improve grey decision-making models.

Decision-making problems in emergency plan selection for epidemic prevention and control (EPAC) are generally characterized by risky and uncertainty due to multiple possible emergency states and vagueness of decision information. In the process of emergency plan selection for EPAC, it is necessary to consider several obvious features, i.e. different states of epidemics, dynamic evolvement process of epidemics and decision-makers' (DMs') psychological factors such as risk preference and loss aversion.

In this paper, a novel decision-making method based on cumulative prospect theory (CPT) is proposed to solve emergency plan selection of an epidemic problem, which is generally regarded as hybrid-information multi-attribute decision-making (HI-MADM) problems in major epidemics. Initially, considering the psychological factors of DMs, the expectations of DMs are chosen as reference points to normalize the expectation vectors and decision information with three different formats. Subsequently, the matrix of gains and losses is established according to the reference points. Furthermore, the prospect value of each alternative is obtained and the comprehensive prospect values of alternatives under different states are calculated. Accordingly, the ranking of alternatives can be obtained.

The validity and robustness of the proposed method are demonstrated by a case calculation of emergency plan selection. Meanwhile, sensitivity analysis and comparison analysis with fuzzy similarity to ideal solution (FTOPSIS) method and TODIM (an acronym in Portuguese for interactive and MADM) method illustrate the effectiveness and superiority of the proposed method.

An emergency plan selection method is proposed for EPAC based on CPT, taking into account the psychological factors of DMs.

Highlights

1. This paper proposes a new CPT-based EDM method for EPAC under a major epidemic considering the psychological factorsof DMs, such as risk preference, loss aversion and so on.

2. The authors' work gives approaches of normalization, comparison and distance measurement for dealing with the integration of three hybrid formats of attributes.

3. This article gives some guidance, which contributes to solve the problems of risk-based hybrid multi-attribute EDM.

4. The authors illustrate the advantages of the proposed method by a sensitivity analysis and comparison analysis with existing FTOPSIS method and TODIM method.

This paper proposes a new CPT-based EDM method for EPAC under a major epidemic considering the psychological factorsof DMs, such as risk preference, loss aversion and so on.

The authors' work gives approaches of normalization, comparison and distance measurement for dealing with the integration of three hybrid formats of attributes.

This article gives some guidance, which contributes to solve the problems of risk-based hybrid multi-attribute EDM.

The authors illustrate the advantages of the proposed method by a sensitivity analysis and comparison analysis with existing FTOPSIS method and TODIM method.

The purpose of this paper is to propose an integrated decision-making model for multi-attributes decision-making (MADM) problems in additive manufacturing (AM) process planning and for related MADM problems in other research areas.

This research analyzed the drawbacks of former methods and then proposed two sub-decision-making models, “deviation model” and “similarity model”. The former sub-model aimed to measure the deviation extent of each alternative to the aspired goal based on analyzing Euclidean distance between them, whereas the latter sub-model applying grey incidence analysis was used to measure the similarity between alternatives and the expected goal by investigating the curve shape of each alternative. Afterwards, an integrated model based on the aggregation of the two sub-models was proposed and verified by a numerical example and simple case studies.

The calculating results of the cited numerical example and the comparison to former related research showed that this proposed model is more practical and reasonable than former methods applied in MADM problems of AM. In addition, the proposed model can be applied in other fields where MADM problems exist.

This proposed integrated model not only considered the deviation extent of alternatives to the aspired goal but also investigated the similarity between alternatives and the expected goal. The similarity analysis compensates the drawbacks of traditional “distance-based” models or methods that cannot distinguish alternatives which have the same distance-based index value.

One of the key success factors for an organization is the promotion of qualified personnel for vacant positions. Especially, the promotion of middle and senior managers play an important role in terms of organization’s success. In personnel promotion problem in which the candidates are nominated within the organization and they have been working for a specific period of time and are known in their organization, the candidates should be evaluated based on their recent as well as past performances to make right selection for the vacant position. For this reason, the purpose of this paper is to propose an integrated dynamic multi-attribute decision-making (MADM) model based on intuitionistic fuzzy set for solving personnel promotion problem.

The proposed model integrates analytic hierarchy process (AHP) technique and the dynamic evaluation by intuitionistic fuzzy operator for personnel promotion. AHP is employed to determine the weight of attributes based on decision maker’s opinions, and the dynamic operator is utilized to aggregate evaluations of candidates for different years. Atanassov’s intuitionistic fuzzy set theory is utilized to represent uncertainty and vagueness in MADM process.

A numerical example is presented to show the applicability of the proposed method for personnel promotion problem and a sensitivity analysis is conducted to demonstrate efficiency of dynamic evaluation. The findings indicate that the varying weights of years employed determined the best candidate for promotion.

The novelty of this study is defining personnel promotion as a MADM problem in the literature for the first time and proposing an integrated dynamic intuitionistic fuzzy MADM approach for the solution, in which the candidates are evaluated at different years.

The purpose of this paper is to determine which criteria should be taken into account while choosing face masks for pandemic times and to what extent their effects are.

Nine face mask alternatives were evaluated based on the assessments of their performance with respect to twelve attributes. Seven experts were asked to evaluate the mask alternatives and the influences among attributes. In gathering expert judgments, spherical fuzzy number-based linguistic terms were utilized in the study to provide a more comprehensive representation domain to them.

According to the results, the most important attributes are found as material type, cost and bacteria–virus protection level. The best face mask is N95, which is followed by respirators and surgical masks.

The implication of the research is to evaluate face masks in terms of criteria such as physical, performance, protection and cost to decide on what basis they were selected as a personal protective equipment (PPE) based on expert assessments. This is useful in selection of the right face mask with optimum performance and provides guidance to the general public and profession specific groups for this purpose. The face mask companies might be also benefitted from the implications of the present study in their design and research and development (R&D) operations.

The preference ranking of the face mask alternatives has not been studied in detail yet in the literature. Focusing on this issue, the present study provides a comprehensive assessment of the selection criteria of face masks in the pandemic era.

The invention and use of mobile commerce (m-commerce) technology have progressed in recent years. In small to medium-sized enterprises (SMEs), the decision to implement business-to-business m-commerce is a multiple-criteria decision analysis problem that involves both qualitative and quantitative factors, and its evaluation may be based on imprecise information or uncertain data. Furthermore, there may be significant dependences or important feedback among different levels of criteria or alternatives. However, most conventional decision models cannot capture these complex interrelationships. The purpose of this paper is to adopt a new hybrid multiple attribute decision model (MADM) model to evaluate the implementation of business-to-business m-commerce by SMEs in Taiwan to enhance the thinking of management and improve decision gaps.

In this study, the authors present the use of a new hybrid MADM combined with a decision-making trial and evaluation laboratory (DEMATEL) method to construct an influential network relationship map (INRM) and find the influential weights of DANP (DEMATEL-based ANP) in criteria from the influential relationship matrix, and the modified VIKOR method using influential weights to evaluate and integrate the criteria performance in the gaps and to analyze how to reduce the gaps to evaluate the decision to implement business-to-business m-commerce by SMEs based on INRM.

The findings of using the new hybrid MADM model can efficiently and successfully be applied to the business-to-business m-commerce of SMEs to improve and reduce the performance gaps among each criterion/aspect when setting improvement strategies for achieving an aspiration level based on INRM.

This study achieves the following: successfully building a decision network (called an influential network relation map (INRM)) of the technological advances and implementations of business-to-business m-commerce for solving the inter-dependence and feedback of criteria/aspects in the real world problem; how changing effective solutions from existing performance of situations/alternatives into aspiration levels to fit the current competitive markets in the business-to-business m-commerce of SMEs; and efficiently shifting from ranking and selection when determining the most preferable approaches to performance improvement by modified VIKOR methods.