Spatial multicriteria decision support for robust land-use suitability: The case of landfill site selection in Northeastern Greece

Multicriteria spatial decision support systems (MC-SDSS) have emerged as an integration of geographical information systems (GIS) and multiple criteria decision aid (MCDA) methods for incorporating conflicting objectives and decision makers’ preferences into spatial decision models. In this paper, we present spatial UTASTAR (S-UTASTAR), a raster-based MC-SDSS for land-use suitability analysis. The multicriteria component of the system is based on the UTA-type disaggregation-aggregation approach. S-UTASTAR is applied in a raster-based case study concerning land-use suitability analysis to identify appropriate municipal solid waste landfill (MSW) sites in Northeast Greece. Moreover, robustness analysis tools are implemented to guarantee robust decision support results. More specifically, during the aggregation phase, the Stochastic Multiobjective Acceptability Analysis (SMAA) is used to indicate the frequency at which a site achieves the best ranking positions within a large set of alternative landfill sites.     

An MCDA approach for the selection of bike projects based on structuring and appraising activities

This paper presents an MCDA approach for the structuring and appraising activities of a large and complex decision problem. More specifically, the paper makes use of the three-step structuring process for decision analysis proposed by von Winterfeldt and Edwards: (1) identifying the problem; (2) selecting an appropriate analytic approach; and (3) developing a detailed analytic structure. For illustration of the approach a case study dealing with the assessment task of prioritising and selecting initiatives and projects from a public pool with limited funds is examined throughout the paper. The process is embedded in a Decision Support System (DSS) making use of the REMBRANDT technique for pair wise comparisons to determine project rankings. A procedure for limiting the number of pair wise comparisons to be made in the process is in this connection presented. Finally, strengths and weaknesses in the approach are discussed and conclusions are made.     

Structuring an MCDA model using SSM: A case study in energy efficiency

This work presents the use of a problem structuring method, Soft Systems Methodology (SSM), to structure a Multi-Criteria Decision Analysis (MCDA) model, aimed at appraising energy efficiency initiatives. SSM was useful to help defining clearly the decision problem context and the main actors involved, as well as to unveil the relevant objectives for each stakeholder. Keeney’s Value Focused Thinking approach was then used to refine and structure the list of objectives according to the perspective of the main evaluators identified. In addition to describing this particular case study, this paper aims at providing some general guidelines on how SSM may facilitate the emergence of objectives for MCDA models.     

Weighted Influence Non-linear Gauge System (WINGS) – An analysis method for the systems of interrelated components

The WINGS method has been derived from DEMATEL and can be widely used as a structural model for analysis of intertwined factors and causal relations between them. Its novelty comes from an idea of including in one mathematical mechanism both strength (importance) and influence of the system components. In particular, WINGS can be applied as the MCDA method for evaluating alternatives when interrelations between criteria cannot be neglected. For the problem with independent criteria, WINGS reproduces the additive aggregation of preferences, a classical method in MCDA.     

Preference disaggregation and statistical learning for multicriteria decision support: A review

Disaggregation methods have become popular in multicriteria decision aiding (MCDA) for eliciting preferential information and constructing decision models from decision examples. From a statistical point of view, data mining and machine learning are also involved with similar problems, mainly with regard to identifying patterns and extracting knowledge from data. Recent research has also focused on the introduction of specific domain knowledge in machine learning algorithms. Thus, the connections between disaggregation methods in MCDA and traditional machine learning tools are becoming stronger. In this paper the relationships between the two fields are explored. The differences and similarities between the two approaches are identified, and a review is given regarding the integration of the two fields.     

Tentative guidelines to help choosing an appropriate MCDA method

Despite the development of a large number of refined multicriterion decision aid (MCDA) methods, none can be considered as the `super method' appropriate to all decision making situations. Hence, how can one choose an appropriate method to a specific decision situation? Recent experimental studies in psychology and behaviour have revealed, on the one hand, that the human thinking is not to be modelled by logical rules and calculations, and, on the other hand, that the response mode affects the preference formation as well as the use of compensatory or noncompensatory strategies. The aim of this paper is to draw a conceptual framework for articulating tentative guidelines to choose an appropriate MCDA method. This paper also presents the results of the comparison of well known multicriterion aggregation procedures (MCAP) on the basis of these guidelines. In our opinion this study can constitute a first step for proposing a methodological approach to select an appropriate MCDA method to a specific decision making situation. Such an approach should be validated and may be integrated into a decision support system. Moreover, the framework suggested is helpful to develop useful methods and to address neglected issues within the field.     

Preference disaggregation: 20 years of MCDA experience

The philosophy of preference disaggregation in multicriteria decision-aid systems (MCDA) is to assess/infer global preference models from the given preferential structures and to address decision-aiding activities. This paper presents a panorama of preference disaggregation methods and summarises the most important results and applications over the last 20 years.     

Model choice in multicriteria decision aid

The purpose of this paper is to illustrate, using a real case study, one of the points stressed in the “Manifesto of the new Multi Criteria Decision Aid (MCDA) era” (Bouyssou et al., 1993) regarding the application of the basic theory of MCDA procedures. Although the great diversity of MCDA procedures may be seen as a strong point, it can be a weakness, and a systematic analysis of decision procedures if one method makes more sense than another for a specific problem is necessary. The problem of selecting the most appropriate (MCDA) technique for a particular application is in itself a MCDA problem since the decision making criteria used for the selection are different and conflicting in nature. In this paper three selection models are implemented to assist the system analyst, when confronted with a multi-objective decision problem, to select the most appropriate MCDA technique for application to the problem of optimal ranking of water development projects in an arid country. These models are developed by Deason (1984), Gershon (1981), and Tecle (1988). Results indicated that PROMETHEE was the most preferred method for this problem.     

A data model for algorithmic multiple criteria decision analysis

Various software tools implementing multiple criteria decision analysis (MCDA) methods have appeared over the last decades. Although MCDA methods share common features, most of the implementing software have been developed independently from scratch. Majority of the tools have a proprietary storage format and exchanging data among software is cumbersome. Common data exchange standard would be useful for an analyst wanting to apply different methods on the same problem. The Decision Deck project has proposed to build components implementing MCDA methods in a reusable and interchangeable manner. A key element in this scheme is the XMCDA standard, a proposal that aims to standardize an XML encoding of common structures appearing in MCDA models, such as criteria and performance evaluations. Although XMCDA allows to present most data structures for MCDA models, it almost completely lacks data integrity checks. In this paper we present a new comprehensive data model for MCDA problems, implemented as an XML schema. The data model includes types that are sufficient to represent multi-attribute value/utility models, ELECTRE III/TRI models, and their stochastic extensions, and AHP. We also discuss use of the data model in algorithmic MCDA.     

Multicriteria decision analysis (MCDA): Central Porto high-speed railway station

Over recent years, Portugal has been working towards their integration in the trans-European high-speed railway network. While in Spain several new high-speed lines are already under construction or beginning operation, in Portugal the necessary studies are still being carried out. One of these studies concerned the location of one of the high-speed railway stations to be built in the city of Porto, meant to connect the second most populated metropolitan area in Portugal to the high-speed railway network. The goal for the study was to compare alternative siting strategies, defined by the Portuguese high-speed railway authority. These strategies were materialized in a set of location alternatives, which were evaluated from a range of technical, economical, social and environmental criteria. This paper describes the multicriteria decision analysis (MCDA) approach by which the best alternative was identified from the given set of possible alternatives.     

University objectives and socioeconomic results: A multicriteria measuring of alignment

Universities develop technology transfer mechanisms as the tools required to undertake missions committed to the socioeconomic environment. In this work a new proposal to measure the extent to which the goals or strategic objectives of a university are aligned with the results obtained through its technology transfer mechanisms with the local community is presented. This will enable to perform a diagnosis, by comparing the situation sought by the University Management team (expected case) with the actual one that derives from the application of the plans that implement the technology transfer mechanisms (real case). To achieve this, two different Multicriteria Decision Analysis techniques e.g. Analytic Network Process (ANP) and Analytic Hierarchy Process (AHP) will be used. Both the methodology and the MCDA techniques proposed need to be explained and clarified to the different experts who collaborate in the study, hence the facilitating process, key to the whole procedure, will be analysed in detail.The model proposed in this study is applied to analyse the case of the National University of Colombia – Bogotá Campus. Findings show that the following questions can be answered: (i) How much importance is granted by the University Management to the objectives of the University? (ii) To what extent are the objectives of the university fulfilled by the technology transfer mechanisms to the socioeconomic environment? (iii) Are the objectives of the university aligned with the results achieved through the technology transfer mechanisms?     

Using a multi-criteria decision aid methodology to implement sustainable development principles within an organization

The implementation of Sustainable Development (SD) within an Organization is a difficult task. This is due to the fact that it is difficult to deal with conflicting and incommensurable aspects such as environmental, economic and social dimensions. In this paper we have used a Multi-Criteria Decision Aid (MCDA) methodology to cope with these difficulties. MCDA methodology offers the opportunity to avoid monetary valuation of the different dimensions of the SD. These dimensions are not substitutable for one another and all have a role to play. There is an abundance of possible aggregation procedures in MCDA methodology. In this paper we have proposed an innovative method to choose a suitable aggregation procedure for SD problems. Real life case studies of the implementation of an outranking approach (i.e., ELECTRE) and of a mono-criterion synthesis approach (i.e., MAUT approaches based on the Choquet integral) were done to respectively rank 22 SD strategic actions within an expertise Institute and rank 20 practical operational actions to control energy consumption of the Institute’s buildings.     

PROMETHEE: A comprehensive literature review on methodologies and applications

In recent decades, several Multi-Criteria Decision Aid (MCDA) methods have been proposed to help in selecting the best compromise alternatives. In the meantime, the PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluations) family of outranking methods and their applications has attracted much attention from academics and practitioners. In this paper, a classification scheme and a comprehensive literature review are presented in order to uncover, classify, and interpret the current research on PROMETHEE methodologies and applications. Based on the scheme, 217 scholarly papers from 100 journals are categorized into application areas and non-application papers. The application areas include the papers on the topics of Environment Management, Hydrology and Water Management, Business and Financial Management, Chemistry, Logistics and Transportation, Manufacturing and Assembly, Energy Management, Social, and Other Topics. The last area covers the papers published in several fields: Medicine, Agriculture, Education, Design, Government and Sports. The scholarly papers are also classified by (1) year of publication, (2) journal of publication, (3) authors’ nationality, (4) PROMETHEE as applied with other MCDA methods, and (5) PROMETHEE as applied with GAIA (Geometrical Analysis for Interactive Aid) plane. It is hoped that the paper can meet the needs of researchers and practitioners for easy references of PROMETHEE methodologies and applications, and hence promote the future of PROMETHEE research.     

Multicriteria classification and sorting methods: A literature review

The assignment of alternatives (observations/objects) into predefined homogenous groups is a problem of major practical and research interest. This type of problem is referred to as classification or sorting, depending on whether the groups are nominal or ordinal. Methodologies for addressing classification and sorting problems have been developed from a variety of research disciplines, including statistics/econometrics, artificial intelligent and operations research. The objective of this paper is to review the research conducted on the framework of the multicriteria decision aiding (MCDA). The review covers different forms of MCDA classification/sorting models, different aspects of the model development process, as well as real-world applications of MCDA classification/sorting techniques and their software implementations.     

A synergy of multicriteria techniques to assess additive value models

The assessment of additive value functions in Multicriteria Decision Aid (MCDA) has to face issues of legitimacy and technical difficulties when real decision makers are involved. This paper presents a synergy of three complementary techniques to assess additive models on the whole criteria space. The synergy includes a revised MACBETH technique, the standard MAUT trade-off analysis and UTA-based methods for the assessment of both the marginal value functions and the weighting factors. The paper uses a set of original robustness measures and rules associated with revised MACBETH and UTA in order to manage multiple linear programming solutions and to extract robust conclusions from them. Finally, to illustrate the methods’ synergy, an application example is presented, dealing with the planning of metro extension lines.     

Behavioural decision theory for multi-criteria decision analysis: a guided tour

Multi-criteria decision analysis (MCDA) involves asking decision makers difficult questions, and can leave them thinking that their judgements are not as coherent as they might have thought. This experience can be distressing and may even lead to rejection of the analysis. The psychology of preference sheds light both on how people naturally make choices without decision analytic assistance, and on how people think about the MCDA elicitation questions. As such, it can help the analyst to respond helpfully to difficulties which decision makers may face. In this paper, we review research from Behavioural Decision Theory relevant to MCDA. Our review follows the MCDA process, discussing research relevant to the structuring, value elicitation, and weighting phases of the analysis, outlining relevant and important findings, and open questions for research and practice.     

On the construction of mutual fund portfolios: A multicriteria methodology and an application to the Greek market of equity mutual funds

The evaluation of the performance of mutual funds (MFs) has been a very interesting research topic not only for researchers, but also for managers of financial, banking and investment institutions. In this paper, an integrated methodological framework for the evaluation of MF performance is proposed. The proposed methodology is based on the combination of discrete and continuous multicriteria decision aid (MCDA) methods for MFs selection and composition. In the first stage of the analysis the UTADIS MCDA method is employed in order to develop mutual fund's performance models supporting the selection of a small set of MFs, which will compose the final portfolios. In the second stage, a goal programming model is employed to determine the proportion of the selected MFs in the final portfolios. The methodology is applied on data of Greek MFs over the period 1999–2001 with encouraging results.     

A general decomposition approach for multi-criteria decision trees

In this paper, we address the dynamic and multi-criteria decision-making problems under uncertainty, generally represented by multi-criteria decision trees. Decision-making consists of choosing, at each period, a decision that maximizes the decision-maker outcomes. These outcomes should often be measured against a set of heterogeneous and conflicting criteria. Generating the set of non-dominated solutions is a common approach considered in the literature to solve the multi-criteria decision trees, but it becomes very challenging for large problems. We propose a new approach to solve multi-criteria decision trees without generating the set of all non-dominated solutions, which should reduce the computation time and the cardinality of the solution set. In particular, the proposed approach combines the advantages of decomposition with the application of multi-criteria decision aid (MCDA) methods at each decision node. A generalization of the Bellman’s principle of decomposition to the multi-criteria context is put forward. A decomposition theorem is therefore proposed. Under the sufficient conditions stated by the theorem, the principle of decomposition will generate the set of best compromise strategies. Seven MCDA methods are then characterized (lexicographic, weighted sum, multi-attribute value theory, TOPSIS, ELECTRE III, and PROMETHEE II) against the conditions of the theorem of decomposition and against other properties (neutrality, anonymous, fidelity, dominance, independency), in order to confirm or infirm their applicability with the proposed decomposition principle. Moreover, the relationship between independency and temporal consistence is discussed as well as the effects of incomparableness, rank reversals, and use of thresholds. Two conjectures resulted from this characterization.     

Modelling of linguistic variables in multicriteria energy policy support

The climate change and the increasing complexity of the energy sector along with the prerequisite for sustainability have broadened the energy policy shaping field by bringing out new challenges. Decision support tools and methods, such as Multicriteria Decision Aid (MCDA), are necessary for energy policy, in the pursuit of appropriate approaches necessary to support the restructuring of the energy sector, concerning patterns of energy extraction, generation, transformation and use, from unsustainable to sustainable forms of development. Papers devoted to the investigation of MCDA models using linguistic variables for energy policy support seem to be not available in the international literature. The scope of this paper is to explore different linguistic representation and computational models in MCDA that are or can be applied to energy policy support and to establish a clear linkage between them. This paper argues that MCDA methodologies with direct computation on linguistic variables can support energy policy frameworks, bridging the gap between energy policy makers thinking, reasoning, representation and computing. Finally, current trends, open questions and prospects in this topic are pointed out.     

Extending the use of scenario planning and MCDA for the evaluation of strategic options

Multi-criteria decision analysis (MCDA) is well equipped to deal with conflicting, qualitative objectives when evaluating strategic options. Scenario planning provides a framework for confronting uncertainty, which MCDA lacks. Integration of these methods offers various advantages, yet its effective application in evaluating strategic options would benefit from scenarios that reflect a larger number of wide-ranging scenarios developed in a time-efficient manner, as well as incorporation of MCDA measures that inform within and across scenario comparison of options. The main contribution of this paper is to illustrate how a more diverse set of scenarios could be developed quickly, and to investigate how regret could be used to facilitate comparison of options. First, the reasons for these two areas of development are elaborated with respect to existing techniques. The impacts of applying the proposed method in practice are then assessed through a case study involving food security in Trinidad and Tobago. The paper concludes with a discussion of findings and areas for further research.