Match!

Robust Ordinal Regression

Published on Jan 17, 2014
· DOI :10.1002/9780470400531.eorms1090
Salvatore Corrente15
Estimated H-index: 15
(University of Catania),
Salvatore Greco52
Estimated H-index: 52
(University of Catania)
+ 1 AuthorsRoman Slowifiski67
Estimated H-index: 67
(PUT: Poznań University of Technology)
Cite
Abstract
Within disaggregation–aggregation approach, ordinal regressionaims at inducing parameters of a preference model, for example, parameters of a value function, which represent some holistic preference comparisons of alternatives given by the Decision Maker (DM). Usually, from among many sets of parameters of a preference model representing the preference information given by the DM, only one specific set is selected and used to work out a recommendation. For example, while there exist many value functions representing the holistic preference information given by the DM, only one value function is typically used to recommend the best choice, sorting, or ranking of alternatives. Since the selection of one from among many sets of parameters compatible with the preference information given by the DM is rather arbitrary, robust ordinal regressionproposes taking into account all the sets of parameters compatible with the preference information, in order to give a recommendation in terms of necessary and possible consequences of applying all the compatible preference models on the considered set of alternatives. In this chapter, we present the basic principle of robust ordinal regression, and the main multiple criteria decision methods to which it has been applied. In particular, UTA GMS and GRIPmethods are described, dealing with choice and ranking problems, then UTADIS GMS , dealing with sorting (ordinal classification) problems. Next, we present robust ordinal regression applied to Choquet integral for choice, sorting, and ranking problems, with the aim of representing interactions between criteria. This is followed by a characterization of robust ordinal regression applied to outranking methods and to multiple criteria group decisions. Finally, we describe an interactive multiobjective optimization methodology based on robust ordinal regression, and an evolutionary multiobjective optimization method, called NEMO, which is also using the principle of robust ordinal regression.
  • References (93)
  • Citations (81)
Cite
References93
Newest
Silvia Angilella10
Estimated H-index: 10
(University of Catania),
Salvatore Corrente15
Estimated H-index: 15
(University of Catania)
+ 1 AuthorsRoman Slowifiski67
Estimated H-index: 67
(PUT: Poznań University of Technology)
Abstract We are considering the problem of measuring and analyzing customer satisfaction concerning a product or a service evaluated on multiple criteria. The proposed methodology generalizes the MUSA (MUlticriteria Satisfaction Analysis) method. MUSA is a preference disaggregation method that, following the principle of ordinal regression analysis, finds an additive utility function representing both the comprehensive satisfaction level of a set of customers and a marginal satisfaction level wi...
Salvatore Corrente15
Estimated H-index: 15
(University of Catania),
Salvatore Greco52
Estimated H-index: 52
(University of Catania),
Roman Slowifiski67
Estimated H-index: 67
(PUT: Poznań University of Technology)
Robust Ordinal Regression (ROR) supports Multiple Criteria Decision Process by considering all sets of parameters of an assumed preference model, that are compatible with preference information elicited by a Decision Maker (DM). As a result of ROR, one gets necessary and possible preference relations in the set of alternatives, which hold for all compatible sets of parameters, or for at least one compatible set of parameters, respectively. In this paper, we propose an extension of ELECTRE and PR...
Miłosz Kadziński16
Estimated H-index: 16
(PUT: Poznań University of Technology),
Salvatore Greco52
Estimated H-index: 52
(University of Catania),
Roman Slowifiski67
Estimated H-index: 67
(PUT: Poznań University of Technology)
In this paper, we present a new preference disaggregation method, called RUTA, which infers a set of additive value functions from the preference information referring to the desired ranks of some reference alternatives. Real-life experience indicates that people willingly refer to the range of allowed ranks that a particular alternative should attain, or to constraints on the final scores of the alternatives. We develop a mathematical model for incorporating such preference information via mixe...
Published on Jul 1, 2013in European Journal of Operational Research3.81
Miłosz Kadziński16
Estimated H-index: 16
(PUT: Poznań University of Technology),
Tommi Tervonen16
Estimated H-index: 16
(EUR: Erasmus University Rotterdam)
We consider a problem of ranking alternatives based on their deterministic performance evaluations on multiple criteria. We apply additive value theory and assume the Decision Maker’s (DM) preferences to be representable with general additive monotone value functions. The DM provides indirect preference information in form of pair-wise comparisons of reference alternatives, and we use this to derive the set of compatible value functions. Then, this set is analyzed to describe (1) the possible an...
Published on Jul 1, 2013in Journal of Global Optimization1.63
Miłosz Kadziński16
Estimated H-index: 16
(PUT: Poznań University of Technology),
Roman Slowifiski67
Estimated H-index: 67
(PUT: Poznań University of Technology)
In this paper, we present a new preference disaggregation method for multiple criteria sorting problems, called DIS-CARD. Real-life experience indicates the need of considering decision making situations in which a decision maker (DM) specifies a desired number of alternatives to be assigned to single classes or to unions of some classes. These situations require special methods for multiple criteria sorting subject to desired cardinalities of classes. DIS-CARD deals with such a problem, using t...
Published on May 1, 2013in Group Decision and Negotiation2.01
Miłosz Kadziński16
Estimated H-index: 16
(PUT: Poznań University of Technology),
Salvatore Greco52
Estimated H-index: 52
(University of Catania),
Roman Slowifiski67
Estimated H-index: 67
(PUT: Poznań University of Technology)
In this paper, we introduce the concept of a representative value function in a group decision context. We extend recently proposed methods UTAGMS-GROUP and UTADISGMS-GROUP with selection of a compromise and collective preference model which aggregates preferences of several decision makers (DMs) and represents all instances of preference models compatible with preference information elicited from DMs. The representative value function is built on results of robust ordinal regression, so its rep...
Published on Apr 25, 2013
Eleftherios Siskos6
Estimated H-index: 6
(NTUA: National Technical University of Athens),
Michail Malafekas1
Estimated H-index: 1
(NTUA: National Technical University of Athens)
+ 1 AuthorsJohn Psarras32
Estimated H-index: 32
(NTUA: National Technical University of Athens)
E-government benchmarking is being conducted by various organizations but its assessment is based on a limited number of indicators and does not highlight the multidimensional nature of the electronically provided services. This paper outlines a multicriteria evaluation system based on four points of view: (1) infrastructures, (2) investments, (3) e-processes, and (4) users’ attitude in order to evaluate European Union countries. In this paper, twenty one European Union countries are evaluated a...
Published on Apr 1, 2013 in DSS (Decision Support Systems)
Miłosz Kadziński16
Estimated H-index: 16
(PUT: Poznań University of Technology),
Tommi Tervonen16
Estimated H-index: 16
(EUR: Erasmus University Rotterdam)
We present a new approach for multiple criteria sorting problems. We consider sorting procedures applying general additive value functions compatible with the given assignment examples. For the decision alternatives, we provide four types of results: (1) necessary and possible assignments from Robust Ordinal Regression (ROR), (2) class acceptability indices from a suitably adapted Stochastic Multicriteria Acceptability Analysis (SMAA) model, (3) necessary and possible assignment-based preference...
Published on Mar 1, 2013in Journal of Mathematical Economics0.63
Alfio Giarlotta7
Estimated H-index: 7
(University of Catania),
Salvatore Greco52
Estimated H-index: 52
(University of Catania)
A classical approach to model a preference on a set A of alternatives uses a reflexive, transitive and complete binary relation, i.e. a total preorder. Since the axioms of a total preorder do not usually hold in many applications, preferences are often modeled by means of weaker binary relations, dropping either completeness (e.g. partial preorders) or transitivity (e.g. interval orders and semiorders). We introduce an alternative approach to preference modeling, which uses two binary relations–...
José Rui Figueira29
Estimated H-index: 29
(Technical University of Lisbon),
Salvatore Greco52
Estimated H-index: 52
(University of Catania)
+ 1 AuthorsRoman Slowifiski67
Estimated H-index: 67
(PUT: Poznań University of Technology)
We present main characteristics of ELECTRE (ELimination Et Choix Traduisant la REalite - ELimination and Choice Expressing the REality) family methods, designed for multiple criteria decision aiding. These methods use as a preference model an outranking relation on the set of actions—it is constructed in result of concordance and nondiscordance tests involving a specific input preference information. After a brief description of the constructivist conception in which the ELECTRE methods are inse...
Cited By81
Newest
Sally Giuseppe Arcidiacono1
Estimated H-index: 1
(University of Catania),
Salvatore Corrente15
Estimated H-index: 15
(University of Catania),
Salvatore Greco52
Estimated H-index: 52
(University of Catania)
Abstract The level dependent Choquet integral has been proposed to handle decision making problems in which the importance and the interaction of criteria may depend on the level of the alternatives’ evaluations. This integral is based on a level dependent capacity, which is a family of single capacities associated to each level of evaluation for the considered criteria. We present two possible formulations of the level dependent capacity where importance and interaction of criteria are constant...
Published on Apr 1, 2019in European Journal of Operational Research3.81
Salvatore Greco52
Estimated H-index: 52
(University of Catania),
Alessio Ishizaka23
Estimated H-index: 23
+ 1 AuthorsGianpiero Torrisi7
Estimated H-index: 7
(University of Catania)
Abstract We propose a methodology to employ composite indicators for performance analysis of units of interest using and extending the family of Stochastic Multiattribute Acceptability Analysis. We start evaluating each unit by means of weighted sums of their elementary indicators in the whole set of admissible weights. For each unit, we compute the mean, μ , and the standard deviation, σ , of its evaluations. Clearly, the former has to be maximized, while the latter has to be minimized as it de...
Published on Jun 1, 2019in Expert Systems With Applications4.29
Mengzhuo Guo (Ministry of Education), Mengzhuo Guo (Ministry of Education)+ 0 AuthorsJiapeng Liu4
Estimated H-index: 4
(Ministry of Education)
Abstract A new decision-aiding approach for multiple criteria sorting problems is proposed for considering the non-monotonic relationship between the preference and evaluations of the alternatives on specific criteria. The approach employs a value function as the preference model and requires the decision maker (DM) to provide assignment examples of a subset of reference alternatives as preference information. We assume that the marginal value function of a non-monotonic criterion is non-decreas...
Published on May 1, 2019in European Journal of Operational Research3.81
Dimitrios Angelopoulos2
Estimated H-index: 2
(NTUA: National Technical University of Athens),
Yannis Siskos24
Estimated H-index: 24
(UniPi: University of Piraeus),
John Psarras32
Estimated H-index: 32
(NTUA: National Technical University of Athens)
Abstract Electricity demand forecasting is an essential process in the operation and planning procedures of power systems that considerably influences the decisions of utility providers. Main aim of this paper is, first, to examine the relationship between a time series and influential multiple criteria, and, second, to provide long-term electricity demand forecasts in Greece. An original disaggregation or ordinal regression analysis methodological framework is outlined to optimally assess a rob...
Published on Jan 1, 2019
Ana Sara Costa (University of Lisbon), Isabella Maria Lami7
Estimated H-index: 7
(Polytechnic University of Turin)
+ 2 AuthorsJosé Luis Borbinha14
Estimated H-index: 14
(University of Lisbon)
In this chapter, we consider a decision problem related to cultural adaptive reuse of abandoned buildings in Turin, an Italian big city. We propose to handle this decision problem by considering several criteria and by using a recently proposed nominal classification method called Cat-SD (Categorization by Similarity–Dissimilarity). The case study is presented in detail in order to illustrate the advantages of the proposed method. The chapter starts by presenting an overview of the Cat-SD method...
Published on Jan 1, 2019
Michał K. Tomczyk2
Estimated H-index: 2
(PUT: Poznań University of Technology),
Miłosz Kadziński16
Estimated H-index: 16
(PUT: Poznań University of Technology)
Published on Jan 1, 2019
Michalis Doumpos3
Estimated H-index: 3
,
Constantin Zompounidis47
Estimated H-index: 47
In multicriteria decision aiding, preference disaggregation analysis involves the inference of preferential information from holistic judgments that the decision maker provides. This area of research has attracted strong interest and various methodologies have been proposed over the past three decades for different types of decision problems and multicriteria models. This chapter overviews the developments and perspective in this field, covering established techniques as well as the state-of-the...
Published on Nov 1, 2018in European Journal of Operational Research3.81
Ana Sara Costa2
Estimated H-index: 2
(IST: Instituto Superior Técnico),
José Rui Figueira29
Estimated H-index: 29
(IST: Instituto Superior Técnico),
José Luis Borbinha1
Estimated H-index: 1
(IST: Instituto Superior Técnico)
Abstract In this paper, we propose a new multiple criteria decision aiding method for nominal classification problems, where the categories are predefined and no order exists among them. A multiple criteria nominal classification problem consists of assigning actions, assessed according to multiple criteria, to nominal categories. The new method, designated Cat-SD ( Cat egorization by Similarity-Dissimilarity), is based on the concepts of similarity and dissimilarity. We propose a way of modelin...
Published on Mar 1, 2018in European Journal of Operational Research3.81
Jiapeng Liu4
Estimated H-index: 4
(Ministry of Education),
Xiuwu Liao11
Estimated H-index: 11
(Huda: Hubei University)
+ 1 AuthorsJian-Bo Yang51
Estimated H-index: 51
(University of Manchester)
We propose a novel approach to address a multiple criteria sorting (MCS) problem with an imbalanced set of assignment examples. The approach employs a piecewise-linear additive value function as the preference model and adopts the disaggregation–aggregation paradigm to infer a sorting model from provided assignment examples on a set of reference alternatives. We utilize a hierarchical clustering algorithm and several linear programming models to identify reference alternatives that are active to...
Published on Jan 1, 2018
Nikolaos F. Matsatsinis21
Estimated H-index: 21
(TUC: Technical University of Crete),
Evangelos Grigoroudis24
Estimated H-index: 24
(TUC: Technical University of Crete),
Eleftherios Siskos6
Estimated H-index: 6
(NTUA: National Technical University of Athens)
The philosophy of preference disaggregation in multicriteria decision analysis encapsulates the assessment/inference of preference models, from given preferential structures, and the implementation of decision aid activities through consistent and robust operational models. This chapter presents a new outlook on the well-known UTA method, which is devoted to the elicitation of values through the inference of multiple additive value models. On top of that, it incorporates the latest theoretical d...
View next paperOrdinal regression revisited: Multiple criteria ranking using a set of additive value functions