Bernard Roy

Bio: Bernard Roy is an academic researcher from Paris Dauphine University. The author has contributed to research in topics: ELECTRE & Preference. The author has an hindex of 47, co-authored 150 publications receiving 12226 citations. Previous affiliations of Bernard Roy include University of Paris & La Poste.

The outranking approach and the foundations of electre methods

Abstract: In the first part of this paper, we describe the main features of real-world problems for which the outranking approach is appropriate and we present the concept of outranking relations. The second part is devoted to basic ideas and concepts used for building outranking relations. The definition of such outranking relations is given for the main ELECTRE methods in Part 3. The final part of the paper is devoted to some practical considerations.

Aide multicritère à la décision : méthodes et cas

Abstract: 1. page 38, l1–2 lire « si et seulement si H = T ∪ V est complète, transitive, T est la partie asymétrique de H et V est la partie symétrique de H. », 2. page 39, l-4 lire « si et seulement si H = T ∪ V est complète, de Ferrers, quasitransitive, T est la partie asymétrique de H et V est la partie symétrique de H. », 3. page 62, l1 lire « la façon », 4. page 101, l6 lire « l’axiome de non-redondance assure la validité », 5. page 156, l-6 avant 3.1.6 lire « il suffit de changer », 6. page 174, l-3 lire « k3 = 7/10 », 7. page 194, l-3 lire «⇒ [Non(xpPyp)] », 8. page 249, Figure 5.2.1. Remplacer la première légende (schéma en haut à gauche) par « bSa et Non(aSb) », 9. page 285, formule (r.5.3.11) deuxième ligne lire « ≤ gj(b) + vj [gj(b)] », 10. page 287, l-4 lire « tel que dk(b, a) < c(b, a) », 11. page 312, l-10 lire « d’actions incomparables », 12. page 325, l-2 de la note 1 lire « Barrett » 13. page 386, Figure 6.2.3. Supprimer l’arc de a1 vers a7, 14. page 394, l2 du cas iii) Lire « l’unique catégorie Cx+1 », 15. page 421, l19 lire « pour λ2 < λ1 »,

Méthodologie multicritère d'aide à la décision

Abstract: Note: Bibliogr. : p. 407-412. Index Reference Record created on 2004-09-07, modified on 2016-08-08

The Analytic Hierarchy Process

Abstract: This chapter provides an overview of Analytic Hierarchy Process (AHP), which is a systematic procedure for representing the elements of any problem hierarchically. It organizes the basic rationality by breaking down a problem into its smaller constituent parts and then guides decision makers through a series of pair-wise comparison judgments to express the relative strength or intensity of impact of the elements in the hierarchy. These judgments are then translated to numbers. The AHP includes procedures and principles used to synthesize the many judgments to derive priorities among criteria and subsequently for alternative solutions. It is useful to note that the numbers thus obtained are ratio scale estimates and correspond to so-called hard numbers. Problem solving is a process of setting priorities in steps. One step decides on the most important elements of a problem, another on how best to repair, replace, test, and evaluate the elements, and another on how to implement the solution and measure performance.

Graph theory with applications

Abstract: (1977). Graph Theory with Applications. Journal of the Operational Research Society: Vol. 28, Volume 28, issue 1, pp. 237-238.

Evolutionary algorithms for solving multi-objective problems

Abstract: List of Figures. List of Tables. Preface. Foreword. 1. Basic Concepts. 2. Evolutionary Algorithm MOP Approaches. 3. MOEA Test Suites. 4. MOEA Testing and Analysis. 5. MOEA Theory and Issues. 3. MOEA Theoretical Issues. 6. Applications. 7. MOEA Parallelization. 8. Multi-Criteria Decision Making. 9. Special Topics. 10. Epilog. Appendix A: MOEA Classification and Technique Analysis. Appendix B: MOPs in the Literature. Appendix C: Ptrue & PFtrue for Selected Numeric MOPs. Appendix D: Ptrue & PFtrue for Side-Constrained MOPs. Appendix E: MOEA Software Availability. Appendix F: MOEA-Related Information. Index. References.

Estimation and Inference in Econometrics

Abstract: Offering a unifying theoretical perspective not readily available in any other text, this innovative guide to econometrics uses simple geometrical arguments to develop students' intuitive understanding of basic and advanced topics, emphasizing throughout the practical applications of modern theory and nonlinear techniques of estimation. One theme of the text is the use of artificial regressions for estimation, reference, and specification testing of nonlinear models, including diagnostic tests for parameter constancy, serial correlation, heteroscedasticity, and other types of mis-specification. Explaining how estimates can be obtained and tests can be carried out, the authors go beyond a mere algebraic description to one that can be easily translated into the commands of a standard econometric software package. Covering an unprecedented range of problems with a consistent emphasis on those that arise in applied work, this accessible and coherent guide to the most vital topics in econometrics today is indispensable for advanced students of econometrics and students of statistics interested in regression and related topics. It will also suit practising econometricians who want to update their skills. Flexibly designed to accommodate a variety of course levels, it offers both complete coverage of the basic material and separate chapters on areas of specialized interest.

Survey of multi-objective optimization methods for engineering

Abstract: A survey of current continuous nonlinear multi-objective optimization (MOO) concepts and methods is presented. It consolidates and relates seemingly different terminology and methods. The methods are divided into three major categories: methods with a priori articulation of preferences, methods with a posteriori articulation of preferences, and methods with no articulation of preferences. Genetic algorithms are surveyed as well. Commentary is provided on three fronts, concerning the advantages and pitfalls of individual methods, the different classes of methods, and the field of MOO as a whole. The Characteristics of the most significant methods are summarized. Conclusions are drawn that reflect often-neglected ideas and applicability to engineering problems. It is found that no single approach is superior. Rather, the selection of a specific method depends on the type of information that is provided in the problem, the user’s preferences, the solution requirements, and the availability of software.