Computational Intelligence Techniques for Multicriteria Decision Aiding: An Overview

Doumpos, Michael; Zopounidis, Constantin

doi:10.1002/9781118522516.ch1

Cited by 18 publications

(30 citation statements)

References 105 publications

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“…In the literature, a rich variety of MCDA techniques are available for utilization, such as the Multi-Attribute Utility Theory (MAUT) [21], Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) [22,23], ELECTRE [24], and the Analytic Hierarchy Process (AHP) [25,26]. To handle uncertainty, concepts from probability [27], fuzzy sets [28], and grey numbers [23] have been incorporated into some of the MCDA methods. Because so many different types of MCDA methods are available for employment by decision makers, one must select the most suitable technique to use in a given situation.…”

Section: Methods and Datamentioning

confidence: 99%

Elimination Method of Multi-Criteria Decision Analysis (MCDA): A Simple Methodological Approach for Assessing Agricultural Sustainability

et al. 2017

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Abstract:In the present world context, there is a need to assess the sustainability of agricultural systems. Various methods have been proposed to assess agricultural sustainability. Like in many other fields, Multi-Criteria Decision Analysis (MCDA) has recently been used as a methodological approach for the assessment of agricultural sustainability. In this paper, an attempt is made to apply Elimination, a MCDA method, to an agricultural sustainability assessment, and to investigate its benefits and drawbacks. This article starts by explaining the importance of agricultural sustainability. Common MCDA types are discussed, with a description of the state-of-the-art method for incorporating multi-criteria and reference values for agricultural sustainability assessment. Then, a generic description of the Elimination Method is provided, and its modeling approach is applied to a case study in coastal Bangladesh. An assessment of the results is provided, and the issues that need consideration before applying Elimination to agricultural sustainability, are examined. Whilst having some limitations, the case study shows that it is applicable for agricultural sustainability assessments and for ranking the sustainability of agricultural systems. The assessment is quick compared to other assessment methods and is shown to be helpful for agricultural sustainability assessment. It is a relatively simple and straightforward analytical tool that could be widely and easily applied. However, it is suggested that appropriate care must be taken to ensure the successful use of the Elimination Method during the assessment process.

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Section: Methods and Datamentioning

confidence: 99%

Elimination Method of Multi-Criteria Decision Analysis (MCDA): A Simple Methodological Approach for Assessing Agricultural Sustainability

et al. 2017

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“…The preference (called outranking ) of an alternative over another is determined by means of a concordance‐nondiscordance rule. Such a rule checks whether the former is at least as good as the latter on a sufficiently strong coalition of criteria and whether there is no criteria on which the former alternative is unacceptably worse than the latter. For a detailed presentation of such methods, the reader is referred to Doumpos and Zopounidis () and Zopounidis and Doumpos ().…”

Section: Introductionmentioning

confidence: 99%

“…Several learning algorithms were proposed in the MCDA literature, in particular based on linear programing. It is the case of the UTADIS method developed by Jacquet‐Lagrèze and Siskos () (see also Doumpos and Zopounidis, , Chapter 4).…”

Section: Introductionmentioning

confidence: 99%

Learning monotone preferences using a majority rule sorting model

Sobrie

Mousseau

Pirlot

2018

Int Trans Operational Res

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We 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.

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“…During that analysis, they learn and can become a tool expert, for example, supporting decision-making. This tool has been successfully used in many financial decision-making problems, which include (Doumpos, Zopounidis, & Pardalos, 2012):…”

Section: Artificial Neural Network In the Area Of The Portfolio Manamentioning

confidence: 99%

The New Portfolio Management Process in the Context of the Use of Artificial Neural Networks

Halicki¹

2017

JEW

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The main objective of this article is to draw attention to the subject of portfolio management process, which is often not discussed in the professional literature. It has been shown that globalization affects the portfolio management process, which is presented in the literature in a similar manner. Thus, in this publication, the presentation of the process was made in terms of the classical one, and then the attempt was made to establish its form after the evolution that results from the above mentioned globalization. In addition, this new form is presented from the perspective of the use of artificial neural networks as organizations which invest cash primarily in financial instruments should take into account the mentioned expert tool for the purpose of further development. The publication also shows the key areas which the professional literature focuses on with regards to the subject of portfolio management. The study used the literature from the area of portfolio management, which is the basis for theoretical consideration, but these results have got the cognitive and practical value. They are a basis for separate quantitative research, and the proposed portfolio management process model can be considered cognitively interesting for researchers and investors.

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Computational Intelligence Techniques for Multicriteria Decision Aiding: An Overview

Cited by 18 publications

References 105 publications

Elimination Method of Multi-Criteria Decision Analysis (MCDA): A Simple Methodological Approach for Assessing Agricultural Sustainability

Elimination Method of Multi-Criteria Decision Analysis (MCDA): A Simple Methodological Approach for Assessing Agricultural Sustainability

Learning monotone preferences using a majority rule sorting model

The New Portfolio Management Process in the Context of the Use of Artificial Neural Networks

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