ELECTRE TRI Method Research Articles

Economic feasibility for selecting wastewater treatment systems.

The ideal configuration of wastewater treatment system (WTS) for attending cities specificities has become a complex decision, due to the fact that there are several available technologies, and a diversity of characteristics presented in the scenario of each city. Considering the importance of economic analysis, especially in developing countries, this work aims to demonstrate the economic feasibility considering cost-related indicators for the ideal WTS selection for specific features in these cities. Based on a literature review, 37 main WTS and two economic cost-related indicators (Net Present Value and Annualized Net Present Value) were considered. First of all, using a multi-criteria analysis these WTS were grouped in classes using the ELECTRE TRI method, based on criteria related to efficiency, and the weights were defined by appointments from research specialists in the literature appointments. The economic analysis was performed using the Monte Carlo Simulation (MCS) method, which has been applied specifically to each WTS class, thus generating a framework of economic viability for this context. The WTS with low and high costs were appointed, considering the development level in each applied scenario. This work contributes to expanding the WTS study horizons to select an ideal system, considering the economic aspect.

Estimation of the profiles in posteriori ELECTRE TRI: A mathematical programming model

Priori ELECTRE TRI is a multi-criteria sorting method which places the existing alternatives in a series of predefined categories. Each category is known by two profiles that delineate the upper and lower limits of the category, and for every criterion, these profiles have a predefined value. In this paper, the ELECTRE TRI method is considered in the state of posteriori, in which, the expert first assigns the existing alternatives to the categories, and after that the value of each profile for each criterion is determined. The aim of this study is finding profiles in which all the other parameters (thresholds and cutting levels) are pre-defined. To determine the value of each criterion for each profile, a new mixed-integer nonlinear programming model (MINLP) is proposed whose objective is to maximize the lowest credibility for every profile relative to the alternatives assigned to the categories. Due to the complexity of the problem, a heuristic method and a particle swarm optimization meta-heuristic are proposed to solve the problem. Some instances of FINRISK.BDF from ELECTRE TRI software are studied to compare and evaluate the proposed methods. According to the computational experiments, the particle swarm optimization algorithm outperforms the heuristic method and can be used to solve large-scale problems effectively.

Decision making on supplier selection based on social, ethical, and environmental criteria: A study in the textile industry

The main objective of this paper is to balance social, environmental and economic criteria, alongside related ethical issues, in the supplier selection process when outsourcing activities in the textile industry. We propose a multi-criteria model to support supplier selection process, whereby suppliers are allocated to classes based on sustainability, integrating the opinions of customers and managers. The model has three phases: i) criteria definition, in which the Copeland method is used to aggregate criteria reported in the literature for a group of decision makers (customers and expert managers); ii) elicitation of the perceptions of decision-makers, about criteria and the definition of weights for these criteria using the AHP method, and iii) multi-criteria classification of suppliers performed using the ELECTRE-TRI method. A numerical application was performed in the textile sector in order to test results. The main results show that suppliers can be classified, balancing social, environmental and economic criteria and related ethical issues, considering opinions from customers and experts. The theoretical implications can benefit researchers who can apply the model in future research into economic, environmental and social interactions. Managers can use the structure presented in this model to improve supplier selection.

Learning monotone preferences using a majority rule sorting model

AbstractWe consider the problem of learning a function assigning objects into ordered categories. The objects are described by a vector of attribute values and the assignment function is monotone w.r.t. the attribute values (monotone sorting problem). Our approach is based on a model used in multicriteria decision analysis (MCDA), called MR‐Sort. This model determines the assigned class on the basis of a majority rule and an artificial object that is a typical lower profile of the category. MR‐Sort is a simplified variant of the ELECTRE TRI method. We describe an algorithm designed for learning such a model on the basis of assignment examples. We compare its performance with choquistic regression, a method recently proposed in the preference learning community, and with UTADIS, another MCDA method leaning on an additive value function (utility) model. Our experimentation shows that MR‐Sort competes with the other two methods, and leads to a model that is interpretable.

An application of a multi-criteria decision support system to assess energy performance of school buildings

This work presents a multi-criteria classification system considering multiple, conflicting and incommensurate evaluation aspects influencing energy efficiency in school buildings. The multi-criteria ELECTRE TRI method is used to classify energy performance of school buildings into categories of merit using the IRIS software. The alternatives under evaluation are assigned to predefined ordered categories according to their absolute performance and not in comparison with the performance of other alternatives. Each alternative is assessed using reference profiles defining the boundaries of the categories in which the alternatives should be sorted. The model was applied using a set of performance indicators obtained in the framework of a research and development project aimed at assessing the energy performance of a sample of Portuguese school buildings. IRIS allowed inferring robust conclusions by indicating the range of categories for each alternative, considering the decision maker's preferences, captured by the parameters of ELECTRE TRI.

A multi-criteria approach to sort and rank policies based on Delphi qualitative assessments and ELECTRE TRI: The case of smart grids in Brazil

This work presents a methodology to perform a multi-criteria decision analysis based on qualitative assessments from multiple experts or stakeholders. The application that motivated these methodological developments is also described, consisting of an assessment of policies to foster technological innovations in the electricity sector, namely in a context of evolution to smart grids. Qualitative assessments were elicited from 28 experts using a Delphi process. The assessments concern the impact of policies on different objectives, but also opinions concerning the importance of these objectives. These opinions are translated into constraints on the weights of the corresponding criteria, in a partial information setting. Then, policies are sorted into categories based on a stochastic multi-criteria analysis for the ELECTRE TRI method. A new ranking approach is also developed to be compatible with the sorting results, based on a robustness analysis of ELECTRE TRI credibility indices. Results are discussed considering the entire set of experts and considering subsets of experts representing different perspectives.

A Multicriteria Approach to the Human Development Index Classification

This paper proposes a new Human Development Index (HDI) classification method using as a basis the same dimensions and weights used by United Nations Development Programme (UNDP), however, avoiding the compensatory effect and misclassification that can occur when UNDP approach is applied. The proposed approach also allows working with any set of dimensions and weights. The classification was performed by the Elimination Et Choix Traidusaint la Realite (ELECTRE TRI), a multicriteria method, in which classes were defined with the visual aid of a non-parametrically tool, the Kernel Density Estimation and the class profiles were calculated by the Jenks Natural Breaks algorithm. The proposed classification method achieved better results than the one adopted by the UNDP, because the countries could be classified accurately in their natural classes without occurring the compensation effect. However, when comparing with the HDI index we have obtained an accuracy of 76.60% for the first proposed model and 78.72% for the second one. Our proposal purely used the same dimensions and weights adopted by UNDP. The proposed method is more robust, closer to reality and can eliminate the compensatory effect between dimensions, thus it can provide more credibility to the HDI. The combination of the ELECTRE TRI method with statistical tools to define classes and class profiles for the HDI is unprecedented in the literature.

A Multicriteria Decision Model for Collaborative Partnerships in Supplier Strategic Management

Maintaining relationships with suppliers has become a critical strategic management issue to business. As a consequence, the tasks of evaluating and selecting suppliers are essential, given that companies delegate part of their business to partners. The main purpose of these tasks is to identify suppliers with the highest potential for meeting a buyer’s needs consistently and at an acceptable overall performance. However these tasks are complex since they involve a variety of conflicting criteria, which makes the problem one that can be tackled by an multicriteria decision aid (MCDA) approach. Moreover, companies have suppliers whose features and performance are different and buyers need to decide at each level how they may best collaborate with each type of supplier. Many papers in the literature have addressed this situation involving supplier selection; nevertheless, most of them present methods to solve ranking and choice problems. The objective of this paper is to propose a model for the strategic management of suppliers which uses the ELECTRE TRI method to sort suppliers into classes of collaboration. Therefore, by using this model it is possible for companies to do so in order to define the most appropriate strategies to adopt for each category.

Multi-criteria approach for products classification and their storage location assignment

Even small improvements in storage operations can bring significant benefits in customer response time, increasing the level of service offered. However, a company cannot offer high level of service for all products. In this sense, one of the ways used to optimize the activities for order picking is the study of storage location assignment problem (SLAP). Thus, this paper proposed a multi-criteria decision model to perform the products classification and to solve the SLAP in a multi-layer warehouse. The ELECTRE TRI method is used to define the shelf level for each product, and the ELECTRE III method is used to establish a fixed location for each product on the shelf it belongs to. The great advantage of this model is that there is not trade-off among the criteria, and it is able to consider several criteria simultaneously. However, the main goal is not optimization, but the search for a storage operations performance balance, considering multiple criteria, allowing for a better inventory management when considering profitability criteria, for example, and improvement in the order picking operations, through the demand and space required criteria. In addition, it considers the preferences of the decision maker.

Sigmoidal Model for Belief Function- Based Electre Tri Method

Sigmoidal Model for Belief Function- Based Electre Tri Method

Applying Multi-Criteria Decision Analysis to the Life-Cycle Assessment of vehicles

This article presents a methodology to classify light-duty vehicles according to their environmental impacts. The classification is based on Life-Cycle Impact Assessment indicators and vehicle operation indicators, which are aggregated using a Multi-Criteria Decision Analysis (MCDA) method. In contrast with most literature combining Life-Cycle Assessment (LCA) and MCDA, vehicles are not compared directly; they are compared to pre-established profiles defining a set of classes. These profiles are established relatively to the impacts of the country's light-duty fleet. The ELECTRE TRI method is chosen for MCDA classification, thus avoiding complete substitutability among criteria and allowing for imprecision in the data. MCDA typically incorporates the subjective values of decision makers, namely through criteria weighting. To obtain conclusions that are not contingent on a given weight vector, we consider a space of weight vectors defined by constraints with a clear rationale and obtain all the possible results compatible with those constraints. The methodology is applied to classify six vehicles available in Portugal with different powertrains: Gasoline and Diesel Internal Combustion Engine Vehicles, Plug-in Hybrid Electric Vehicles (10 and 40-mile battery range) and Battery Electric Vehicle. The discussion suggests how this methodology might be useful for a decision-making entity that wishes to classify vehicles according to their environmental impacts.

The role of financial statements in the prediction of innovative firms: empirical evidence from Greece

This study was undertaken on the basis of reports from international research literature, which indicates that although investments in innovation have a higher return, compared to conventional investments, any relevant information concerning those investments is not distinctly (or clearly) reported on financial statements. The absence of information regarding such investments underlines the inadequacy of financial reporting. In fact, the apparent substitution of official financial statements for other unofficial documents, perhaps even derived from unsafe sources, indicates the negative effects this absence causes on market efficiency. The consequence could be more serious to those investors that are not in the position to seek and use alternative information sources, efficiently. The purpose of this study is to investigate the efficiency of the Electre Tri method in developing models for identifying innovative firms.

Learning criteria weights of an optimistic Electre Tri sorting rule

Multiple criteria sorting methods assign alternatives to predefined ordered categories taking multiple criteria into consideration. The Electre Tri method compares alternatives to several profiles separating the categories. Based on such comparisons, each alternative is assigned to the lowest (resp. highest) category for which it is at least as good as the lower profile (resp. is strictly preferred by the higher profile) of the category, and the corresponding assignment rule is called pessimistic (resp. optimistic). We propose algorithms for eliciting the criteria weights and majority threshold in a version of the optimistic Electre Tri rule, which raises additional difficulties w.r.t. the pessimistic rule. We also describe an algorithm that computes robust alternatives׳ assignments from assignment examples. These algorithms proceed by solving mixed integer programs. Several numerical experiments are conducted to test the proposed algorithms on the following issues: learning ability of the algorithm to reproduce the DM׳s preference, robustness analysis and ability to identify conflicting preference information in case of inconsistencies in the learning set. Experiments show that eliciting the criteria weights in an accurate way requires quite a number of assignment examples. Furthermore, considering more criteria increases the information requirement. The present empirical study allows us to draw some lessons in view of practical applications of Electre Tri using the optimistic rule.

GIS-based photovoltaic solar farms site selection using ELECTRE-TRI: Evaluating the case for Torre Pacheco, Murcia, Southeast of Spain

The Region of Murcia has one of the highest percentages of potential solar radiation in Spain, which puts it in an excellent position to host electricity generation plants through photovoltaic solar systems, commonly known as solar farms. This paper proposes the use of a Geographic Information System (GIS) in order to identify the best plots suitable for installing photovoltaic solar farms in the Municipality of Torre Pacheco, in the southeast of Spain. The plots are classified according to multiple evaluation aspects, by developing a multicriteria model and applying the ELECTRE-TRI method using the Decision Support System IRIS. The combination of GIS and IRIS offers the user the possibility of using the information provided by the GIS mapping leading to an assignment of the feasible courses of action (the plots) to categories of merit according to multiple, conflicting and incommensurate evaluation criteria.The GIS provides a cartographic and alphanumeric database, including two factors of distinct nature: restrictions and criteria. The restrictions are entered into the GIS using layers defined from the current legislation (urban land, undeveloped land, special protection areas for birds, community sites, infrastructures, etc.), which reduce the study area by eliminating those areas in which photovoltaic solar farms cannot be implemented. The criteria are organized into a tree to be used for assessing the greater or lesser capacity to install photovoltaic solar farms. These criteria are introduced into the GIS, taking into account weather, environmental, location, and terrain evaluation aspects.

Multi-criteria sorting methods to select virtual peach ideotypes

The model-based design of virtual fruit ideotypes using multi-objective optimisation algorithms could produce a high number of contrasted fruits. The breeder (decision-maker) will need an automatic tool allowing him/her to sort these contrasted ideotypes into predefined categories corresponding to several targeted traits. This paper aims to develop such a decision-making module to sort a set of fruit ideotypes into one of five preference-ordered categories in the context of brown rot-peach fruit pathosystem. First, a set of ideotypes with contrasted trade-off between three criteria was produced using multi-objective optimisation algorithms. Then, two multi-criteria decision-making methods (ELECTRE-Tri and DRSA: dominance-based rough set approach) were tested in order to reproduce the classification made by the decision-maker. Such a non-typical classification seemed difficult to be reproduced by the ELECTRE-TRI method while the decision rule-based method gave very good results (only 10% wrong assignments). The proposed decision-making tool is very useful to speed-up the model-based design of fruit ideotypes, i.e., breeding.

Electre tri method used to storage location assignment into categories

Day after day, the importance of a company having an efficient storage location assignment system increases. Moreover, since products have different warehouse costs and customers' requirements are also different, it is important to sort products in order to adopt strategies for inventory management that are appropriate for each product. However, adopting a policy for each product is not applicable in the real world. Therefore, companies usually categorize products into classes and thereafter adopt specific inventory management policies. Given this situation, this paper puts forward the arguments for adopting a multi-criteria method, Electre TRI, to sort products that both considers criteria relating to the characteristics of a product as to its physical location in the warehouse and the criteria that are important for inventory strategies, such as, for example, the profitability of each unit held in storage.

Modelo multicritério para avaliação e classificação da gestão organizacional: proposta e caso de uso

Este trabalho tem por objetivo apresentar um modelo multicritério de autoavaliação para a obtenção da classificação do desempenho organizacional à luz das práticas de excelência em gestão. O modelo multicritério proposto se baseia na aplicação do método ELECTRE TRI na obtenção de graus de credibilidade e classificações do desempenho organizacional. Foi efetuada uma aplicação com o objetivo de experimentar a aplicação do modelo proposto. Nessa aplicação, as escalas de avaliação basearam-se em Likert (1932) e os critérios adotados foram inspirados nos seguintes prêmios de excelência em gestão: Prêmio Deming, Malcolm Baldrige, Europeu e PNQ. Como resultado foi possível obter a classificação e, também, identificar os critérios de excelência a serem priorizados, para a elevação da classificação alcançada pela organização.

Improvement of land suitability assessment for agriculture—application in Algeria

The weighted sum already incorporated into a geographical information system (GIS) makes it possible to identify the best lands useful for sustainable agriculture. However, it does not allow for the inclusion of the decision makers’ preferences so that a choice can be made when there are conflicts between decision makers. Because of their spatial aggregation functions, multicriteria decision analysis methods can facilitate decision making in situations where several solutions are available, various criteria have to be taken into account, and decision makers disagree about one point or another. Combinations between ArcGIS and multicriteria analysis methods in this case Elimination Et Choix Traduisant la Realite (ELECTRE TRI) and a version of the weighted sum method simple additive weighting, applicable to the vector data model, have been established. The parameters and the classification system of Food and Agriculture Organization are used in this work. This approach has been tested on the area of Mleta in Algeria. Land suitability maps for durum wheat have been produced. Through the comparison between results obtained by these two methods and those available in a classical method, based on manual overlay procedures, it appears that optimistic procedure of the ELECTRE TRI method is better suited to the problem of land suitability for agriculture.

Prioritization of rehabilitation interventions for urban water assets using multiple criteria decision-aid methods

The aim of this paper is to compare sorting and ranking methods for prioritization of rehabilitation interventions of sewers, taking into account risk, performance and cost. For that purpose multiple criteria decision-aid (MCDA) methods such as ELECTRE TRI for sorting and ELECTRE III for ranking are applied in a real case-study and the results obtained are compared. The case study is a small sanitary sewer system from a Portuguese utility located in the metropolitan area of Lisbon. The problem to investigate is the prioritization of the sewer candidates for rehabilitation. The decision maker (a panel group of specialists) has chosen five assessment measures: water level and maximum flow velocity (hydraulic performance indices), sewer importance and failure repair cost (collapse-related consequences of failure) and the risk of collapse. The results show that the outcomes from ELECTRE III are easier to understand than those from ELECTRE TRI method. Two different sets of weights were used, and the sorting and ranking results from both methods were found to be sensitive to them. ELECTRE TRI method is not straightforward as it involves technical parameters that are difficult to define, such as reference profiles and cut levels.

Integration of MultiCriteria Decision Analysis in GIS to develop land suitability for agriculture: Application to durum wheat cultivation in the region of Mleta in Algeria

Due to constant decrease in farmlands, it is important to identify the best lands useful for sustainable agriculture (productive and profitable agriculture that protects the environment and that is socially equitable). This requirement has resulted in the development of land suitability maps for agriculture by combining several factors of various natures and of differing importance. The integration of MultiCriteria Decision Analysis approaches (MCDA) in a Geographical Information System (GIS) provides a powerful spatial decision support system which offers the opportunity to efficiently produce these land suitability maps. Indeed, GIS is a powerful tool for analyzing spatial data and establishing a process for decision support. Because of their spatial aggregation functions, MCDA methods can facilitate decision making in situations where several solutions are available, various criteria have to be taken into account and decision-makers are in conflict (Dias et al., 2002). The parameters and the classification system used in this work are inspired from the FAO (Food and Agriculture Organization) approach dedicated to a sustainable agriculture. A spatial decision support system has been developed for establishing the land suitability map for agriculture. It incorporates the multicriteria analysis method ELECTRE Tri (ELimitation Et Choix Traduisant la REalité) in a GIS (ArcGIS) within the GIS program package environment. This approach has been tested on the area of Mleta in Algeria. A land suitability map for durum wheat has been produced. Through the obtained results, it appears that ELECTRE Tri method, integrated into ArcGIS 9.2 of ESRI, is better suited to the problem of land suitability for agriculture. The time saving during the development of the land suitability map for the agriculture of the durum wheat was considerable. The coherence of the obtained maps confirms the system effectiveness.