An algorithm for ordinal sorting based on ELECTRE with categories defined by examples

Abstract This work proposes a Progressive Assisted Sorting Algorithm (PASA) based on a multicriteria evaluation ELECTRE-type method. The purpose of the PASA is to aid a decision maker to progressively sort a set of alternatives into a set of categories, which we considered are ordered (ordinal sorting), following a consistency principle. We consider the principle that if an alternative outranks (is as good as) a second one, then it must belong to the same category or to a better category. The set of alternatives already sorted by the decision maker will implicitly define the categories, and will constrain the range of categories where other alternatives may be sorted. We show how the same idea may be used in an aggregation/disaggregation approach, considering some parameters of ELECTRE are not fixed a priori, but are constrained only by the examples provided. In this context, we establish a "convex-shape property" stating that the range of possible categories for an alternative is always an interval of categories. A discussion contrasting this approach with ELECTRE TRI is included in the conclusions

Combining machine learning and metaheuristics algorithms for classification method PROAFTN

© Crown 2019. The supervised learning classification algorithms are one of the most well known successful techniques for ambient assisted living environments. However the usual supervised learning classification approaches face issues that limit their application especially in dealing with the knowledge interpretation and with very large unbalanced labeled data set. To address these issues fuzzy classification method PROAFTN was proposed. PROAFTN is part of learning algorithms and enables to determine the fuzzy resemblance measures by generalizing the concordance and discordance indexes used in outranking methods. The main goal of this chapter is to show how the combined meta-heuristics with inductive learning techniques can improve performances of the PROAFTN classifier. The improved PROAFTN classifier is described and compared to well known classifiers, in terms of their learning methodology and classification accuracy. Through this chapter we have shown the ability of the metaheuristics when embedded to PROAFTN method to solve efficiency the classification problems

Preference Disaggregation: Towards an Integrated Framework

La desagregació de preferències pretén capturar models de preferències mitjançant la descomposició de la informació obtinguda a partir de preferències indirectes que estan en forma d'eleccions holístiques o judicis. Des d'una perspectiva d'ajuda a la presa de decisions multi criteri, aquesta informació es pren com a punt de partida en un procés d'inferència que condueix a model de preferències basat en punts de vista, generalment conflictius, que conjuntament formen una base per a la decisió. L'estudi de les decisions humanes ha rebut una atenció creixent en els últims anys des de diverses disciplines, que inclouen des de les ciències del comportament (anàlisi de decisions, desagregació de preferències), la intel·ligència artificial (aprenentatge de preferències), fins a l'economia i el màrqueting (teoria de l'elecció). Les tres corrents, encara que originades per diferents filosofies, convergeixen ràpidament cap a una comprensió integral de les preferències, que és l'element bàsic per a les decisions i accions humanes. Aquesta tesi doctoral aprofundeix en aquesta àrea de recerca mitjançant la introducció d'un marc analític integrat que permet capturar les preferències d'una forma complexa a partir de l'observació d'opcions holístiques, decisions i judicis.La desagregación de preferencias pretende capturar modelos de preferencias mediante la descomposición de la información obtenida con preferencias indirectas que están en forma de elecciones holísticas o juicios. Desde una perspectiva de ayuda a la toma de decisiones multicriterio, dicha información se toma como punto de partida en un proceso de inferencia que conduce a modelo de preferencias basado en puntos de vista, generalmente conflictivos, que conjuntamente forman una base para la decisión. El estudio de las decisiones humanas ha recibido una atención creciente en los últimos años desde varias disciplinas, que incluyen desde las ciencias del comportamiento (análisis de decisiones, desagregación de preferencias), la inteligencia artificial (aprendizaje de preferencias), hasta la economía y el márqueting (teoría de la elección). Las tres corrientes, aunque originadas por diferentes filosofías, convergen rápidamente hacia una comprensión integral de las preferencias, que es el elemento básico para las decisiones y acciones humanas. Esta tesis doctoral profundiza en esta área de investigación mediante la introducción de un marco analítico integrado que permite capturar las preferencias de una forma compleja a partir de la observación de opciones holísticas, decisiones y juicios.Preference disaggregation aims at capturing preference models by decomposing indirect preference information that are in form of holistic choices or judgments. From a multiple criteria decision aiding perspective, such information is taken as input to an inference procedure that yields to a preference model based on all the, usually conflicting, points of view that together form a basis for the judgments. Studying human judgments and choices has received increasing attention in the last few years from several disciplines, including behavioral science (decision analysis, preference disaggregation), artificial intelligence (preference learning), and economics and marketing (choice modeling). The three streams, although originated from different philosophies, are converging rapidly to a comprehensive understanding of human preferences, that is the main element of decisions and actions. This doctoral dissertation sheds light on this phenomenon by introducing an integrated analytical framework that allows capturing preferences of a complex form by observing holistic choices, decisions, and judgments

La valoración de inversiones corporativas desde la perspectiva del capital intelectual : una aproximación multicriterio

El aumento de la complejidad en la definición y posterior adopción de estrategias corporativas, especialmente las relativas a las decisiones de inversión, es uno de los elementos más significativos derivados del escenario económico internacional en el que operan en la actualidad las empresas. Una serie de factores concretos explican esta circunstancia, tales como la intensificación de los problemas de agencia, el carácter multidimensional del factor riesgo, o la naturaleza intangible de buena parte de los beneficios que generan las inversiones de carácter estratégico adoptadas en el marco de la denominada economía del conocimiento. Todos estos factores de complejidad están condicionando la correcta y eficiente asignación de recursos en la empresa y los procesos de decisión que la modelan. Las técnicas financieras clásicas, que abordan la resolución de dichos procesos desde la perspectiva de la optimización de los atributos rentabilidad y riesgo, son en la actualidad criticadas por no considerar determinados beneficios intangibles que se derivan de los proyectos de inversión. El objetivo general de esta tesis doctoral es desarrollar un nuevo enfoque teórico de valoración de inversiones no financieras fundamentado en el constructo ampliamente aceptado de creación de valor de mercado entendido desde una perspectiva integral y completa. Este enfoque implica una redefinición del término creación de valor, incorporando a la generación de valor financiero la creación de valor no financiero o de capital intelectual, a la vista del decisivo protagonismo de los intangibles como fuente de valor y de ventaja competitiva sostenible. El enfoque teórico de valoración propuesto se articula a través de dos métodos de análisis multicriterio: el proceso analítico jerárquico y el proceso analítico en red. Ambos permiten integrar en el estudio tanto los criterios que inciden en la creación de valor financiero, como aquellos que contribuyen a la creación de valor no financiero o de capital intelectual. Esta integración permite que los dos modelos de valoración que aquí se proponen cuantifiquen el valor total que genera cada alternativa de inversión, con el fin de ayudar a los directivos en sus procesos de decisión corporativos. La metodología propuesta se implementa en dos casos de estudio de la industria agroalimentaria andaluza. El primero consiste en la valoración de tres alternativas de sistemas de gestión de la calidad en el sector cárnico y, en el segundo caso, se evalúan las posibles alternativas de sistemas de gestión ambiental en la industria almazarera. Los resultados de la implementación empírica, además de validar los modelos, han evidenciado la conveniencia de considerar los impactos de las inversiones sobre los activos intangibles de la empresa, pues estos determinan en el mundo real la selección de la alternativa de inversión óptima. Los dos métodos de valoración propuestos implican la formalización del proceso de valoración de inversiones no financieras que actualmente siguen los directivos en las empresas...Increasing complexity in terms of defining and subsequently adopting corporate strategies, especially those relating to investment decisions, is one of the most significant issues emerging from the international economic environment in which businesses operate today. A number of specific factors play a part in this situation, such as the intensification of agency problems , the multidimensional nature of the risk factor, or the intangible nature of many of the benefits generated by strategic investments within the so-called ‘knowledge economy’. All these factors of complexity affect the appropriate and efficient allocation of company resources and the decisionmaking processes that determine them. Classical financial techniques that seek to address these processes from the perspective of optimizing risk and return attributes are now criticized because this kind of analysis ignore several key intangible issues also involved in investment projects. The overall objective of this thesis is to develop a new theoretical approach to evaluating nonfinancial investments, based on the widely-accepted concept of ‘creating market value’, understood from a holistic, comprehensive perspective. This approach requires a redefinition of the term ‘value creation’ to incorporate the creation of nonfinancial value or intellectual capital alongside the concept of financial value creation. This reflects the decisive role of intangible benefits as a source of value and sustainable competitive advantage. The proposed theoretical valuation approach is applied via two multicriteria methods: the analytic hierarchy process and the analytic network process. These allow the inclusion in the analysis of both the criteria that influence the creation of financial value as well as those that contribute to the creation of nonfinancial value or intellectual capital. This integration allows the two proposed valuation models to quantify the total value generated by each investment alternative in order to assist decision-makers in corporate decision processes. The proposed methodology is implemented in two case studies of the Andalusian food industry. The first concerns the evaluation of three alternative systems of quality management in the meat sector, and the second case evaluates possible alternatives for environmental management systems in the olive oil industry. The results of the empirical implementation, as well as validating the models, demonstrate the merits of considering the impact of investments on an organization’s intangible assets, as these influence the selection of the optimal investment alternative in the real world. The two proposed methods of assessment involve formalizing the current process of evaluating nonfinancial investments carried out by a company’s decision makers..

Development of bank acquisition targets prediction models

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Mutual funds performance appraisal using stochastic multicriteria acceptability analysis

Mutual fund investors are concerned with the selection of the best fund in terms of performance among the set of alternative funds. This paper proposes an innovative mutual funds performance evaluation measure in the context of multicriteria decision making. We implement a multicriteria methodology using stochastic multicriteria acceptability analysis, on Greek domestic equity funds for the period 2000–2009. Combining a unique dataset of risk-adjusted returns such as Carhart’s alpha with funds’ cost variables,we obtain a multicriteria performance evaluation and ranking of the mutual funds, by means of an additive value function model. The main conclusion is that among employed variables, the sophisticated Carhart’s alpha plays the most important role in determining fund rankings. On the other hand, funds’ rankings are affected only marginally by operational attributes. We believe that our results could have serious implications either in terms of a fund rating system or for constructing optimal combinations of portfolios

Mutual funds performance appraisal using stochastic multicriteria acceptability analysis

Mutual fund investors are concerned with the selection of the best fund in terms of performance among the set of alternative funds. This paper proposes an innovative mutual funds performance evaluation measure in the context of multicriteria decision making. We implement a multicriteria methodology using stochastic multicriteria acceptability analysis, on Greek domestic equity funds for the period 2000–2009. Combining a unique dataset of risk-adjusted returns such as Carhart’s alpha with funds’ cost variables,we obtain a multicriteria performance evaluation and ranking of the mutual funds, by means of an additive value function model. The main conclusion is that among employed variables, the sophisticated Carhart’s alpha plays the most important role in determining fund rankings. On the other hand, funds’ rankings are affected only marginally by operational attributes. We believe that our results could have serious implications either in terms of a fund rating system or for constructing optimal combinations of portfolios

Mutual funds performance appraisal using stochastic multicriteria acceptability analysis

Mutual fund investors are concerned with the selection of the best fund in terms of performance among the set of alternative funds. This paper proposes an innovative mutual funds performance evaluation measure in the context of multicriteria decision making. We implement a multicriteria methodology using stochastic multicriteria acceptability analysis, on Greek domestic equity funds for the period 2000–2009. Combining a unique dataset of risk-adjusted returns such as Carhart’s alpha with funds’ cost variables,we obtain a multicriteria performance evaluation and ranking of the mutual funds, by means of an additive value function model. The main conclusion is that among employed variables, the sophisticated Carhart’s alpha plays the most important role in determining fund rankings. On the other hand, funds’ rankings are affected only marginally by operational attributes. We believe that our results could have serious implications either in terms of a fund rating system or for constructing optimal combinations of portfolios