Outranking Approach Research Articles

Sensibility analysis of MCDA using prospective in Brazilian energy sector

PurposeThe purpose of this paper is to present a hybrid modelling that combines concepts and techniques for scenario building together with a Multi-criteria Decision Aid (MCDA) outranking approach. The paper presents a case to illustrate the proposed methodology.Design/methodology/approachThe research method is a qualitative and quantitative mixture and it is presented as a study case. Bibliographic research is used to construct the theoretical framework. There are a number of studies that develop a sensibility analysis in MCDA modelling; however, none of them explore the robustness of the MCDA solution with use of scenarios variation.FindingsThe methodology allows the criteria that must be taken into account, according to the decision makers’ values and preferences. It is interesting to note that, depending on the scenario, different weights were applied for each criterion, and the performances of alternatives under each criterion has changed as well.Practical implicationsThis need arises in decision problems that are susceptible to the influence of scenario variation.Originality/valueThis proposal was applied to a real case that has taken into account six alternatives, with a prospective analysis of three scenarios, evaluated by four criteria. The authors use prospective scenarios to choose the criterion weights and alternatives evaluation.

A knowledge-based outranking approach for multi-criteria decision-making with hesitant fuzzy linguistic term sets

The modeling and solving of multi-criteria decision-making (MCDM) problems under uncertainty is still a challenging topic. In real-life decision-making, using linguistic terms to represent experts’ judgments is suitable and straightforward since precise quantitative values may often be unavailable or the cost for their computation is too high. The introduction of hesitant fuzzy linguistic term sets (HFLTSs) was motivated by the limitations of prior linguistic fuzzy models and need for richer linguistic tools. However, since their introduction, comparing HFLTSs is still one of the major concerns of researchers in this area. The existing approaches in the literature commonly rely on (1) labels and intervals from the linguistic terms as the central elements of an envelope-based approach or (2) linguistic scale functions as the basis of a distance-based approach. The two approaches retain certain shortcomings resulting information distortion and loss which may inevitably degrade their credibility. In this paper, the authors are involved in the recent proposal of combining outranking approaches with HFLTSs in an MCDM context. After reviewing the existing approaches, an outranking method based on a novel knowledge-based paradigm for comparing HFLTSs is developed. Alternatively, the paradigm's foundations are the introduced concepts of fuzzy preference relations and profiles considering uncertainty degrees in decision makers’ assessments. The paradigm is then associated with a multi-criteria relational clustering (MCRC) algorithm that additionally extracts fuzzy preference relations between the resultant clusters. Last, an illustrative example is given to verify the appropriateness and efficacy of the developed approach and comparisons are made with other existing ones.

An extended outranking approach for multi-criteria decision-making problems with linguistic intuitionistic fuzzy numbers

Linguistic intuitionistic fuzzy numbers (LIFNs), characterized by a linguistic membership degree, linguistic non-membership degree, and linguistic indeterminacy degree, represent a helpful tool for depicting uncertain information under complex environments. This paper focuses on developing an innovative method to address multi-criteria decision-making (MCDM) problems with LIFNs in which the weight information is completely unknown. First, the distance of LIFNs is defined with the aid of linguistic scale functions (LSFs). Second, some extended outranking relationships between each pair of LIFNs are proposed based on the elicitation of the classic relation models. Moreover, a ranking method is constructed to deal with MCDM problems according to the proposed outranking relationships of LIFNs. Finally, an illustrative example concerning coal mine safety evaluation is provided to demonstrate the proposed method, and its feasibility and validity are further verified by a sensitivity analysis and comparison with other existing methods.

Pemilihan Rancangan Roda Gigi Berdasarkan Karakteristik Material dengan Metode Electre

<span class="fontstyle0">Gears is one of machine elements, cylindrical wheels used for transmitting motion and power from one rotary shaft to anothers. The design of the gear is part of the engineering design activities to produce products that are not only superior in terms of technology but produce the design in accordance with the designer. The design of gear involves extensive procedure, complex calculations and many design decision. It is necessary for the design of the gear based on characteristics of material that matches the designer whishes. The characteristics of material on which to base the design include the size of the geometry, the contact stress, bending stress, precision standard and transmission conditions. Selection of gear design to consider the characteristic materials through multi criteria decision making approach. The ELECTRE method is one of MCDM method used to help decision makers choose the best alternative with outranking approach. The results of the analysis with the model ELECTRE is best alternative consists of alternative 3 that has some design criteria includes: contact stress, , bending stress, precision based on the ISO 1328 standard, transmission conditions and the size of the geometry. According to these calcultion , the absolute dominance grading was determined as alternative 3 > alternative 1 > alternative 4 >alternative 2.</span>

An outranking method for multi-criteria group decision making using hesitant intuitionistic fuzzy linguistic term sets

This article proposes an outranking method for group decision-making (GDM) using hesitant intuitionistic fuzzy linguistic term sets (HIFLTSs). By means of HIFLTSs, the flexibility in generating evaluation information under uncertainty can be achieved to a larger extent than intuitionistic fuzzy set s (IFSs) or hesitant fuzzy linguistic term sets (HFLSs). Based on intuitionistic fuzzy support function (IFSF), intuitionistic fuzzy risk function (IFRF) and intuitionistic fuzzy credibility function (IFCF), the net outranking flow index (NOFI) of each alternative are calculated which represents the net outranking character of an alternative over the other. The linguistic scale functions (LSFs) are employed in this paper to conduct the transformation between qualitative information and quantitative data. Finally, an outranking approach is constructed for ranking alternatives in multi-criteria group decision-making (MCGDM) problems, and the approach is demonstrated using a numerical example.

An extension on PROMETHEE based on the typical hesitant fuzzy sets to solve multi-attribute decision-making problem

Purpose The purpose of this paper is to extend the PROMETHEE method under typical hesitant fuzzy information for solving multi-attribute decision-making problem in which there is hesitancy among experts. Design/methodology/approach Different aggregation and distance functions were developed to deal with HFS. But it is rational that different operators applying in existing methods can produce different results. Also, it is difficult for decision makers to select suitable operators. To address the drawback, this paper develops the PROMETHEE method as an outranking approach to accommodate hesitant fuzzy information. Since the proposed method is constructed on the basis of the pair-wise comparisons, it is independent of the aggregation and distance functions. Findings To demonstrate the efficiency and accuracy of the proposed method, the authors provide a numerical example and a comparative analysis. The results indicate that outranking-based methods suggest a better ranking than the aggregation- and distance-based methods. Research limitations/implications The proposed approach does not consider the hesitant fuzzy linguistic information decision-making problem. Practical implications The proposed approach can be applied in many group decision-making problems in which there is hesitancy among experts. Originality/value This paper proposes an extension on PROMETHEE method under hesitant fuzzy information, which has not been reported in the existing academic literature.

An outranking approach based on interval type-2 fuzzy sets to evaluate preparedness and response ability of non-governmental humanitarian relief organizations

After a disaster occurs, national and international non-governmental humanitarian relief organizations (NGOs), as well as the governmental humanitarian relief organizations (GOs), are involved in carrying out the humanitarian relief operations because of insufficiency in recourses such as lack of equipment and human resources. GOs and NGOs play a crucial role in preparedness and response to natural disasters, especially when available resources of them are not enough. The preparedness and response ability of GOs and NGOs aim to minimize the losses and number of affected people. Therefore, the preparedness and response ability of NGOs are becoming more important to support governmental relief activities. In this paper, a hybrid approach, that consists of interval type-2 fuzzy sets, AHP and PROMETHEE, is proposed to evaluate emergency preparedness and response ability performances of NGOs. The proposed hybrid approach is applied to NGOs in Turkey to evaluate their performances, and is conducted in three phases: (1) determination of critical success factors (CSFs) of humanitarian relief logistics management operations, (2) application of interval type-2 fuzzy AHP for obtaining importance weights of CSFs and (3) application of PROMETHEE based on interval type-2 fuzzy sets to evaluate preparedness and response abilities of NGOs.

An integrated failure mode and effect analysis approach for accurate risk assessment under uncertainty

ABSTRACTFailure Mode and Effect Analysis (FMEA) is a reliability analysis technique that plays a prominent role in improving the reliability and safety of systems, products, and/or services. Although commonly used in quality improvement efforts, the conventional Risk Priority Number (RPN) method has been heavily criticized in the literature for its various limitations, such as in failure mode evaluations, risk factor weights, and RPN computation. In this article, we describe the application of an ELECTRE (ELimination Et Choix Traduisant la REalité)-based outranking approach for FMEA within the interval two-tuple linguistic environment. Considering different types of FMEA team members' assessment information, we employ a hybrid averaging operator to construct the group assessment matrix and use a modified ELECTRE method to analyze the group interval two-tuple linguistic data. Furthermore, the new risk-ranking model deals with the subjective and objective weights of risk factors concurrently, considering the degree of importance that each concept has in the risk analysis. The practicality and applicability of the proposed methodology are demonstrated by applying it to a risk evaluation problem of proton beam radiotherapy, and a comparative study is conducted to validate the effectiveness of the new FMEA approach.

Benchmarking deterministic optimization algorithms using an outranking approach

The comparison of optimization algorithms, through different performance measures, is not straightforward and can be perceived as a multi-criteria problem. Performance profiles, although widely used, has some difficulties in comparing deterministic algorithms. In this work, an outranking approach is studied on a set of examples. The outranking relations, based on concordance and discordance matrices for given threshold values, can be translated into a graph that explicits these relations. The results indicate that the proposed approach elucidates the merits and the disadvantages of different solvers.

Precise decisions in Indian energy sector by imprecise evaluation

Purpose – The purpose of this paper is to prioritize Indian energy sector projects, namely, coal, gas, hydro and solar using fuzzy PROMETHHE (F-PROMETHEE) and Visual PROMETHEE applications and multicriteria decision-making (MCDM) analyses. Design/methodology/approach – The MCDM outranking approach of PROMETHEE under fuzzy environment is used. Four projects of energy sector are selected as alternatives and are compared based on various criteria. These criteria selected on the perspectives of life cycle costing (LCC) analysis and related management approaches for prioritizing projects for effective decision-making (DM). The F-PROMETHEE is described and results are also compared with outranking application in Visual PROMETHEE software based on same set of criteria. For better understanding, the graphical representations of the multicriteria problem are also shown using graphical analysis for interactive aid. Findings – On applying F-PROMETHEE on four energy projects, coal and solar projects outrank high and results shows that coal-based project is preferable and should be considered. Research limitations/implications – Here F-PROMETHEE and Visual PROMETHEE are used as MCDM techniques. However, few other MCDM techniques such as ELECTRE and EATWOS can be also explored to outrank Indian energy sector projects. Practical implications – Indian energy sector involves high degree of complexity for effective DM on the front of prioritized investment-related capacity addition through energy projects. Outranking methods like F-PROMETHEE is able to address the criteria to criteria impact on DM support precisely. Social implications – The finding can provide information to the government or public sector regarding various possible investment options on energy projects in India. Originality/value – This paper can be supplement and act as the support for DM in conflicting situations specifically for prioritizing investments on various energy projects, which further can synergize conflicting ideas of various stakeholders of the Indian energy sector.

Developing a User-Based Decision-Aid Framework for Water Storage Systems in Sub-Saharan Africa: The Case of Blue Nile Basin in Ethiopia

The development of water storage schemes in Sub-Saharan Africa (SSA) is considered a major aid for those regions with unequal water distribution, limited accessibility and anticipated climate change impacts. Great attention is given by many SSA countries to set up different water storage schemes that may improve rural and urban development on a national level. The funding for the water storage schemes is often derived from foreign agencies which conduct feasibility studies for the financing of potential investments. Often however, the feasibility studies rely on a single monetary criterion which may not identify the most appropriate water storage in each case. In addition, limited data availability in many SSA countries increases the difficulty of identifying the most suitable storage option. This paper develops a multicriteria framework for the integrated evaluation of water storage strategies in Sub-Saharan African countries. A set of economic, agronomic and opinion-based criteria are assessed through the PROMETHEE II outranking approach. The introduction of crop modeling complements the limited field data available in agronomic criteria and enhances the scientific rigor of the method. Ethiopia is adopted as a representative case of SSA countries where a diverse set of water storage options is currently under construction, often financed by foreign agencies.

Multi-criteria decision-making based on hesitant fuzzy linguistic term sets: An outranking approach

Hesitant fuzzy linguistic term sets (HFLTSs) are introduced to express the hesitance existing in linguistic evaluation as clearly as possible. However, most existing methods using HFLTSs simply rely on the labels or intervals of linguistic terms, which may lead to information distortion and/or loss. To avoid this problem, linguistic scale functions are employed in this paper to conduct the transformation between qualitative information and quantitative data. Moreover, the directional Hausdorff distance, which uses HFLTSs, is also proposed and the dominance relations are subsequently defined using this distance. An outranking approach, similar to the ELECTRE method, is constructed for ranking alternatives in multi-criteria decision-making (MCDM) problems, and the approach is demonstrated using a numerical example related to supply chain management. Because of the inherent features of the directional Hausdorff distance and the defined dominance relations, this approach can effectively and efficiently overcome the hidden drawbacks that may hamper the use of HFLTSs. Finally, the accuracy and effectiveness of the proposed approach is further tested through sensitivity and comparative analyses.

A hierarchical multi-criteria sorting approach for recommender systems

Classification problems refer to the assignment of alternatives to predefined categories. In this work we focus on ordered classification, called sorting, in which the predefined categories indicate several degrees of interest or suitability of alternatives for a certain user. The assignment of alternatives is based on multiple conflicting criteria. This multi-criteria sorting approach is specially interesting for recommender systems aimed at finding the most suitable alternatives for each user. First, we study the ELECTRE-TRI-B sorting method, which follows the outranking approach based on comparing the evaluations of alternatives with the profile limits separating the categories. The complexity of some recommenders systems requires the extension of the classical ELECTRE-TRI-B method to manage a taxonomical organization of the set of criteria. In this paper we consider a set of criteria in the form of a hierarchy. The intermediate criteria in such a hierarchy correspond to different aspects of the recommendation procedure, such as content, context or cost. At each of these criteria, a sorting problem must be solved. Therefore, we propose extending ELECTRE-TRI-B to handle assignments of alternatives on several levels of the hierarchy. A hierarchical procedure for sorting is proposed, called ELECTRE-TRI-B-H. Secondly, the paper explains the integration of ELECTRE-TRI-B-H into a recommender system of touristic activities related to wine, called GoEno-Tur. This system is developed for the region of Tarragona, Catalonia (Spain), which is a well-recognized area of wine and cava production.

An outranking approach for multi-criteria decision-making problems with interval-valued neutrosophic sets

In this paper, a novel outranking approach for multi-criteria decision-making (MCDM) problems is proposed to address situations where there is a set of numbers in the real unit interval and not just a specific number with a neutrosophic set. Firstly, the operations of interval neutrosophic sets and their related properties are introduced. Then some outranking relations for interval neutrosophic numbers (INNs) are defined based on ELECTRE IV, and the properties of the outranking relations are further discussed in detail. Additionally, based on the outranking relations of INNs, a ranking approach is developed in order to solve MCDM problems. Finally, two practical examples are provided to illustrate the practicality and effectiveness of the proposed approach. Moreover, a comparison analysis based on the same examples is also conducted.

An ELECTRE approach for evaluating secondary education profiles: evidence from PISA survey in Serbia

The use of multi-criteria decision making has been recognized as a useful tool for economic applications, especially in the last decade. The aim of our study is to promote the potential of the ELimination Et Choix Traduisant la REalite (ELECTRE) method in the field of economics of education. To evaluate the secondary education profiles in Serbia, we have used PISA data and the ELECTRE multi-level outranking (ELECTRE MLO) approach, as an alternative to commonly used econometric models. We introduce a new outranking relation, which is important for decision makers for two reasons. First, it allows the establishment of an acyclic relation, for which we provide a threshold value, that assures there will be no cycles in the relation graph. Second, the procedure does not require an excessive number of parameters as in other existing ranking methods, which enables an easier understanding, simplified use and less bias in the decision making process. After neutralizing the impact of socio-economic status and regional disparities, we obtain the performance levels for secondary education profiles in Serbia.

An extension of ELECTRE to multi-criteria decision-making problems with multi-hesitant fuzzy sets

In hesitant fuzzy sets (HFSs), which are generalized from fuzzy sets, the membership degree of an element to a set, for which decision-makers hesitate while considering several values before expressing their preferences concerning weights and data, can be assigned one or more possible precise values between zero and one. If two or more decision-makers assign an equivalent value, that value is only counted once. However, situations in which the same value is repeatedly assigned substantially differ from those in which the value appears only once. Therefore, multi-hesitant fuzzy sets (MHFSs) can be used to manage cases in which values are repeated in a single HFS. In this paper, a method for comparing multi-hesitant fuzzy numbers (MHFNs) is presented. Some outranking relations for MHFNs, which are based on traditional ELECTRE methods, are introduced, and several properties are analyzed. For ranking alternatives, we propose an outranking approach to multi-criteria decision-making (MCDM) problems similar to ELECTRE III, where weights and data are in the form of MHFNs. Finally, an example is given to illustrate the developed approach, and its validity and feasibility are demonstrated by a comparison analysis with other existing methods.

Comparing Rankings from Using TODIM and a Fuzzy Expert System

Abstract TODIM is, in its original formulation, an MCDA method developed to solve ranking problems. As an MCDA method TODIM combines the use of a multi-attribute value function as well as elements of the Outranking Approach, being founded on Prospect Theory. Recent advances in TODIM incorporate concepts from Fuzzy Sets. Although modelling multi-criteria decision problems with Fuzzy Sets has been utilized when the available data are imprecise, their use in MCDA is slightly controversial, because the data fuzzification can invalidate the outcome. Following a mixed qualitative-quantitative research strategy, our aim is to prove that for the ranking problems, TODIM can provide better solutions than Fuzzy Sets. Ranks from TODIM are linear, or strong, in a sense that it has no ties between the alternative solutions. The rank obtained with a Fuzzy Expert System can be weaker, that is, it may be a number of ties. The research strategy extends this result to ranking problems with the occurrence of crisp criteria.

An outranking approach for multi-criteria decision-making problems with simplified neutrosophic sets

In this paper, a new outranking approach for multi-criteria decision-making (MCDM) problems is developed in the context of a simplified neutrosophic environment, where the truth-membership degree, indeterminacy-membership degree and falsity-membership degree for each element are singleton subsets in [0,1]. Firstly, the novel operations of simplified neutrosophic sets (SNSs) and relational properties are developed. Then some outranking relations for simplified neutrosophic number (SNNs) are defined, based on ELECTRE, and the properties within the outranking relations are further discussed in detail. Additionally, based on the outranking relations of SNNs, a ranking approach is developed in order to solve MCDM problems. Finally, two practical examples are provided to illustrate the practicality and effectiveness of the proposed approach. Moreover, a comparison analysis based on the same example is also conducted.

Assessment of vulnerability to climate change using a multi-criteria outranking approach with application to heat stress in Sydney

Climate change vulnerability assessment is a complex form of risk assessment which accounts for both geophysical and socio-economic components of risk. In indicator-based vulnerability assessment (IBVA), indicators are used to rank the vulnerabilities of socio-ecological systems (SESs). The predominant aggregation approach in the literature, sometimes based on multi-attribute utility theory (MAUT), typically builds a global-scale, utility function based on weighted summation, to generate rankings. However, the corresponding requirement for additive independence and complete knowledge of system interactions by analyst are rarely if ever satisfied in IBVA.We build an analogy between the structures of Multi-Criteria Decision Analysis (MCDA) and IBVA problems and show that a set of techniques called Outranking Methods, developed in MCDA to deal with criteria incommensurability, data uncertainty and preference imprecision, offer IBVA a sound alternative to additive or multiplicative aggregation. We reformulate IBVA problems within an outranking framework, define thresholds of difference and use an outranking method, ELECTRE III, to assess the relative vulnerability to heat stress of 15 local government areas in metropolitan Sydney. We find that the ranking outcomes are robust and argue that an outranking approach is better suited for assessments characterized by a mix of qualitative, semi-quantitative and quantitative indicators, threshold effects and uncertainties about the exact relationships between indicators and vulnerability.

An outranking approach for multi-criteria decision-making with hesitant fuzzy linguistic term sets

The main purpose of this paper is to suggest an approach of multi-criteria decision-making that combines a hesitant fuzzy linguistic term set (HFLTS) with an outranking method involving systematic comparisons of the assessment values of alternatives for each criterion. A HFLTS is more suitable than the traditional fuzzy linguistic set for describing decision-makers’ preferences when they prefer to use several linguistic terms in expressions. After reviewing existing studies of HFLTSs, a novel outranking relational system of HFLTSs is developed and dominance relations for HFLTSs are introduced using outranking degrees of HFLTSs. In order to verify the efficacy of the developed method, an illustrative example is given and comparisons are made between the proposed method and other existing ones.