Veto values in Group Decision Making within MAUT: aggregating complete rankings derived from dominance intensity measures

We consider a groupdecision-making problem within multi-attribute utility theory, in which the relative importance of decisionmakers (DMs) is known and their preferences are represented by means of an additive function. We allow DMs to provide veto values for the attribute under consideration and build veto and adjust functions that are incorporated into the additive model. Veto functions check whether alternative performances are within the respective veto intervals, making the overall utility of the alternative equal to 0, where as adjust functions reduce the utilty of the alternative performance to match the preferences of other DMs. Dominance measuring methods are used to account for imprecise information in the decision-making scenario and to derive a ranking of alternatives for each DM. Specifically, ordinal information about the relative importance of criteria is provided by each DM. Finally, an extension of Kemeny's method is used to aggregate the alternative rankings from the DMs accounting for the irrelative importance

Assessment of vulnerability to climate change: theoretical and methodological developments with applications to infrastructure and built environment

Assessing vulnerability to climate change can help policymakers in incorporating climate futures in planning and in better allocating adaptation resources. Indicator Based Vulnerability Assessment (IBVA) has been widely used because it is relatively simple to design, implement and communicate. However, this approach faces significant difficulties from conceptual, theoretical and methodological points of view. A number of assumptions are typically made in methods used for aggregation of indicators—a linear, monotonic relationship between indicator and vulnerability; complete compensation between indicators; precise knowledge of vulnerable systems by stakeholders who provide input data for the assessment exercise—none of which usually hold in reality. Following a meta-analysis of the IBVA literature, the thesis proposes a) a general mathematical framework for vulnerability assessment that better identifies sources of uncertainty and non-linearity; b) a new IBVA assessment methodology, and associated computer tool, based on a pair-wise outranking approach borrowed from decision science; the methodology can represent various sources of uncertainty, different degree of compensation between indicators and different types of non-linearity in the relationship between indicators and vulnerability and; c) a system dynamics model, integrated in the above framework, for studying vulnerability of infrastructure systems and better representing the mechanistic interdependency of their components. These methods are applied to a real-life assessment of the vulnerability to sea-level rise of communities and infrastructure systems in Shoalhaven, south of Sydney, at local scale. The assessment is conducted in collaboration with the Shoalhaven council and includes an analysis of the sensitivity of vulnerability rankings to community preferences. In addition, the effect of using an outranking framework on the way vulnerability is conceptualized by stakeholders is critically appraised

Assessment of vulnerability to climate change: theoretical and methodological developments with applications to infrastructure and built environment

Assessing vulnerability to climate change can help policymakers in incorporating climate futures in planning and in better allocating adaptation resources. Indicator Based Vulnerability Assessment (IBVA) has been widely used because it is relatively simple to design, implement and communicate. However, this approach faces significant difficulties from conceptual, theoretical and methodological points of view. A number of assumptions are typically made in methods used for aggregation of indicators—a linear, monotonic relationship between indicator and vulnerability; complete compensation between indicators; precise knowledge of vulnerable systems by stakeholders who provide input data for the assessment exercise—none of which usually hold in reality. Following a meta-analysis of the IBVA literature, the thesis proposes a) a general mathematical framework for vulnerability assessment that better identifies sources of uncertainty and non-linearity; b) a new IBVA assessment methodology, and associated computer tool, based on a pair-wise outranking approach borrowed from decision science; the methodology can represent various sources of uncertainty, different degree of compensation between indicators and different types of non-linearity in the relationship between indicators and vulnerability and; c) a system dynamics model, integrated in the above framework, for studying vulnerability of infrastructure systems and better representing the mechanistic interdependency of their components. These methods are applied to a real-life assessment of the vulnerability to sea-level rise of communities and infrastructure systems in Shoalhaven, south of Sydney, at local scale. The assessment is conducted in collaboration with the Shoalhaven council and includes an analysis of the sensitivity of vulnerability rankings to community preferences. In addition, the effect of using an outranking framework on the way vulnerability is conceptualized by stakeholders is critically appraised

A contribution to multi-criteria decision making in sustainable energy management based on fuzzy and qualitative reasoning

Energy problems are serious problems caused by limited resources and by human activity such as deforestation, water pollution and various other long-term practices that have environmental impact which produces global warming and climate change. These complex problems usually involve multiple conflicting criteria and multiple decision makers. They require the use of multi-criteria decision-making methods to evaluate different types of variables with respect to sustainability factors addressing conflicting economic, technological, social and environmental aspects. These factors, especially social ones, are not always precise, as imprecision and uncertainty are features of the real world. Therefore, in order to provide useful data from experts' assessments, in this thesis a new multi-criteria decision-making method, as a useful tool in energy planning, is presented. This method supports decision makers in all stages of the decision-making process with uncertain values. An exhaustive literature review on multi-criteria decision analysis and energy planning has been conducted in this thesis. First, the in-depth study of criteria and indicators in the energy planning area is presented. Some well-known multi-criteria decision-making methods and their applications are introduced. In these problems, it is often difficult to obtain exact numerical values for some criteria and indicators. In order to overcome this shortcoming, qualitative reasoning techniques integrated with multi-criteria decision-making methods are capable of representing uncertainty, emulating skilled humans, and handling vague situations. This study proposes a Qualitative TOPSIS (Q-TOPSIS) method, which is a new method for ranking multi-criteria alternatives in group decision making. This new method, in its first step, takes into account qualitative data provided by the decision makers' individual linguistic judgments on the performance of alternatives with respect to each criterion, without any previous aggregation or normalization. Then, in its second step, it incorporates the judgments of decision makers into the modified TOPSIS method to generate a complete ranking of alternatives. Three applications of the proposed method in energy planning are presented. In the first case, the application of the Q-TOPSIS method in a case study of renewable energy alternatives selection is presented. These alternatives are ranked and the proposed method is compared with the modified fuzzy TOPSIS method. A simulation of thirty scenarios using different weights demonstrates that the simplicity and interpretability of Q-TOPSIS provides a general improvement over classic TOPSIS in the case of ordinal assessments. Second, a real case study in a social framework to find an appropriate place for wind farm location in Catalonia is presented. In this case different alternatives were proposed based on social actors' preferences for the location of the desired wind farms in a region between the counties of Urgell and Conca de Barbera. Ranking alternatives concludes that an alternative combining two different initial projects is the best option. Using the proposed method to handle a high degree of conflict in group decision making involving multi-dimensional concepts simplified the experts' measurements. Finally, an application to energy efficiency in buildings using the SEMANCO (Semantic tools for carbon reduction in urban planning) platform is presented in order to assess the energy performance and CO2 emissions of projected urban plans at the city level in Manresa. In this case study, an application of Q-TOPSIS helps decision makers to rank different projects with respect to multi-granular quantitative and qualitative criteria and offers outputs which are very easy for decision makers to understand.Los problemas de la energía son problemas graves causados por los recursos limitados y las actividades humanas como la deforestación, contaminación del agua y otras prácticas con efectos a largo plazo. Estas prácticas tienen un gran impacto ambiental y dan lugar al efecto invernadero, que ocasiona el calentamiento global y cambio climático. Los problemas complejos implican generalmente múltiples criterios contradictorios y múltiples decisores. Requieren el uso de métodos toma de decisiones multicriterio para evaluar diferentes tipos de variables con respecto a factores de sostenibilidad, incluyendo aspectos conflictivos económicos, tecnológicos, sociales y ambientales. Estos factores, especialmente los sociales, no siempre son precisos, dado que la imprecisión y la incertidumbre son características del mundo real. Por lo tanto, con el fin de proporcionar datos útiles a partir de evaluaciones de expertos, en esta tesis se presenta un nuevo método de toma de decisiones multicriterio, como una herramienta útil en la planificación de la energía. Este método permite a los decisores utilizar valores con imprecisión en todas las etapas de la toma de decisiones. En esta tesis se ha realizado una revisión exhaustiva de la literatura sobre el análisis de la decisión multicriterio y la planificación de la energía. En primer lugar, se presenta el estudio a fondo de los criterios e indicadores en el área de planificación de la energía. Se introducen algunos de los métodos más conocidos de toma de decisiones multicriterio y sus aplicaciones. En estos problemas, a menudo es difícil obtener valores numéricos exactos para algunos criterios e indicadores. Para superar esta deficiencia, la integración de técnicas de razonamiento cualitativo en métodos de decisión multicriterio permite representar la incertidumbre, emular el trabajo de seres humanos cualificados y manejar situaciones vagas. Este estudio propone un método TOPSIS cualitativo (Q-TOPSIS), que es un nuevo método de ranking de alternativas para la toma de decisiones multicriterio en grupo. Este nuevo método, toma en cuenta los datos cualitativos proporcionados por los juicios lingüísticos individuales de los decisores sin necesidad de previa agregación o normalización. Se presentan tres aplicaciones del método propuesto en la planificación de la energía. En el primer caso, se presenta la aplicación del método Q-TOPSIS en un caso práctico de selección de alternativas de energías renovables. Una simulación de treinta escenarios utilizando diferentes pesos demuestra que la simplicidad y la interpretabilidad de Q-TOPSIS proporcionan una mejora general del TOPSIS clásico en el caso de evaluaciones ordinales. En segundo lugar, se presenta un estudio de un caso real para decidir el lugar apropiado para ubicación de parques eólicos en una zona de Cataluña. En este caso, las distintas alternativas fueron propuestas en base a las preferencias de los actores sociales sobre la ubicación de los parques eólicos deseados en una región entre los condados del Urgell y la Conca de Barberà. El ranking obtenido de las alternativas concluye que la mejor opción es una alternativa que combina dos proyectos iniciales diferentes. La utilización del método propuesto para la decisión en grupo permite manejar un alto grado de conflicto entre conceptos multidimensionales y simplifica las mediciones de los expertos. Por último, se presenta una aplicación a la eficiencia de la energía en edificios mediante la plataforma SEMANCO (Herramientas semánticas para la reducción de carbono en la planificación urbana) para evaluar la eficiencia de la energía y las emisiones de CO2 de planes urbanísticos proyectados en la ciudad de Manresa. En este caso estudio, la aplicación de Q-TOPSIS ayuda a los decisores a realizar el ranking de los diferentes proyectos con respecto a criterios cuantitativos y cualitativos multi-granulares y ofrece resultados fácilmente inteligibles para los decisores

Multi-Criteria Decision Analysis (MCDA) as the basis for the development, implementation and evaluation of interactive patient decision aids

BACKGROUND: In the context of the progressive movement towards patientcentred care, patient-specific decision support is an important focus of interest. Many diagnostic and treatment patient decision aids (PDAs) are now available to help patients make informed choice decisions. An increasing number of these are software-based, with some available online. Multi-Criteria Decision Analysis (MCDA) is a potentially useful technique on which to base a software-assisted PDA, especially when the decision is complex - as is the case in choosing the best treatment for non-small cell lung cancer – but it has so far been relatively little exploited in this area. The use of any from a number of existing MCDA-based software applications in the development and delivery of a MCDA-based interactive PDA can be an effective way of achieving “best-practice” or normative standards of decision making, such as 1) a well-constructed set of decision criteria or 2) logically consistent patient preferences. However, it also involves the use of resources such as the time and cognitive effort involved in decision-making. The comparative evaluation of alternative MCDA-based software applications in developing and delivering a PDA therefore involves trade-offs between decision effectiveness and decision resource criteria moving from the normative to the prescriptive. MCDA is an ideal tool for this meta-evaluation task as well as for the adoption decision itself. AIM: To analyse, as proof of concept, the use of MCDA for the development, implementation and evaluation of interactive PDAs in routine clinical practice. OBJECTIVES: 1. To assess the use with clinicians in the Spanish NHS of two alternative MCDA software applications which implement dissimilar MCDA techniques in the development of a PDA in routine clinical practice; 2. To assess the use with clinicians in the Spanish NHS of the same two alternative MCDA software applications in the implementation of a PDA in an environment replicating actual clinical consultations; 3. To build a meta-multi-criteria decision model based on the Decision Resources Decision Effectiveness Analysis (DRDEA) framework and assess the use of this model by clinicians in the Spanish NHS to make the choice between the two MCDA applications as the basis for a PDA. METHODS: 1) Two dissimilar MCDA software applications served as a basis for the development of a lung cancer clinical management PDA in close collaboration with two different groups of three clinicians from two different Spanish NHS hospitals (H1 and H2): 1) Expert Choice, which implements the Analytic Hierarchy Process (AHP) MCDA approach; 2) Annalisa in Elicia (ALEL), which implements the Simple Attribute Weighting (SAW) MCDA approach. The process of codevelopment of the PDA in hospitals H1 and H2 was documented; 2) Expert Choice was used to implement (i.e. deliver) the lung cancer clinical management PDA in three hypothetical consultations in hospital H1. In each consultation, one of the three clinicians involved in the development of the tool, with support by this researcher, guided a proxy patient (a non-clinical member of hospital staff) through the PDA. The same process was repeated with the MCDA software ALEL in hospital H2. The process of delivery of the PDA in hospitals H1 and H2 was documented; 3) This researcher built a meta-multi-criteria decision model based on the DRDEA framework to help clinicians choose between different MCDA software applications as the basis of a PDA. The MCDA approach used for this meta-model was Multi- Attribute Value Theory (MAVT). The model was implemented, using the software HiView 3, with three clinicians from hospital H3 for the choice between Expert Choice and ALEL as the basis of a lung cancer clinical management PDA. RESULTS: The thesis makes a three-fold contribution to research in patient-centred decision support. First, it presents two new MCDA software-based approaches to clinical decision support, based on joint work with clinicians in the Spanish NHS, for developing an interactive PDA for the clinical management of non-small cell lung cancer. Second, it describes the use of these decision support tools in the delivery of 5 an interactive PDA for the clinical management of non-small cell lung cancer in a hospital environment via simulated consultations between actual clinicians, with support from this researcher, and proxy lung cancer patients. Third, it presents and applies a new MCDA-based methodology for evaluating the use of alternative MCDA software applications in the development and delivery of interactive PDAs

Hierarchical outranking methods for multi-criteria decision aiding

Els mètodes d’Ajut a la Decisió Multi-Criteri assisteixen en la pressa de decisions implicant múltiples criteris conflictius. Existeixen dos enfocaments principals per resoldre aquest tipus de problemes: els mètodes basats en utilitat i d’outranking, cadascun amb les seves fortaleses i debilitats. Els mètodes outranking estan basats en models d’elecció social combinats amb tècniques d’intel·ligència artificial (com gestió de dades categòriques o d’incertesa). Son eines per una avaluació i comparació realista d’alternatives, basant-se en les necessitats i coneixements del prenedor de la decisió. Una de les debilitats dels mètodes outranking és la no consideració de jerarquies de criteris, que permeten una organització natural del problema, distingint diferents nivells de generalitat que modelen les relacions taxonòmiques implícites entre criteris. En aquesta tesi ens enfoquem en el desenvolupament d’eines d’outranking jeràrquiques i la seva aplicació en casos d’estudi reals per problemes de classificació i rànquing.Los métodos de Ayuda a la Decisión Multi-Criterio asisten en la toma de decisiones involucrando múltiples criterios conflictivos. Existen dos enfoques principales para resolver éste tipo de problemas: los métodos basados en utilidad y de outranking, cada uno con sus fortalezas y debilidades. Los métodos outranking están basados en modelos de elección social combinados con técnicas de Inteligencia Artificial (como gestión de datos categóricos o de incertidumbre). Son herramientas para una evaluación y comparación realista de alternativas, basándose en las necesidades y conocimientos del tomador de decisión. Una de las debilidades de los métodos outranking es la no consideración de jerarquías de criterios, que permiten una organización natural del problema, distinguiendo distintos niveles de generalidad que modelan las relaciones taxonómicas implícitas entre criterios. En ésta tesis nos enfocamos en el desarrollo de herramientas de outranking jerárquicas y su aplicación en casos de estudio reales para problemas de clasificación y ranking.Multi-Criteria Decision Aiding (MCDA) methods support complex decision making involving multiple and conflictive criteria. MCDA distinguishes two main approaches to deal with this type of problems: utility-based and outranking methods, each with its own strengths and weaknesses. Outranking methods are based on social choice models combined with Artificial Intelligence techniques (such as the management of categorical data or uncertainty). They are recognized as providing tools for a realistic assessment and comparison of a set of alternatives, based on the decision maker’s knowledge and needs. One of the main weaknesses of the outranking methods is the lack of consideration of hierarchies of criteria, which enables the decision maker to naturally organize the problem, distinguishing different levels of generality that model the implicit taxonomical relations between the criteria. In this thesis we focus on developing hierarchical outranking tools and their application to real-world case studies for ranking and sorting problems

Advancing sustainable nanotechnology with multiple criteria decision aiding

Nanotechnology is currently emerging as the next industrial revolution. It enables the production of goods (i.e. nanoproducts, NPs) with enhanced functionalities, which have nonetheless caused mounting concerns about the potential implications they can have on the environment, economy and society. This thesis employs Multiple Criteria Decision Aiding (MCDA), one form of decision support, to aid the sustainable development of nanotechnology. The first original contribution of this doctoral research is the development of a framework of sustainability assessment criteria for NPs, through a three-phase procedure based on the MCDA process, including a literature review, a pilot and a main survey. It lead to a comprehensive framework of 68 criteria, ranked according to their relative importance, allocated to six main domain areas: (i) economic performance; (ii) environmental impacts; (iii) environmental risk assessment; (iv) human health risk assessment; (v) social implications; and (vi) technical performance. All the criteria are reliable and can be used in real case studies to increase the knowledge about the sustainability of NPs. The second original contribution presented in this thesis is a robust model (DRSA-based model) based on green chemistry principles implementation for the classification of synthesis processes of nanomaterials in preference-ordered classes. This tool was developed through knowledge elicitation techniques based on coconstructive MCDA with the collaboration of two experts (the decision makers) in synthesis of nanomaterials. The robustness of the ensuing model was assessed (and confirmed) by means of another model developed ad hoc (ELECTRE-based model), structured on an MCDA method implementing a stochastic multiple criteria classification strategy. The results confirm that MCDA is an effective decision support approach to foster sustainable development of nanotechnology, providing that the analysts who apply it take these considerations into account. They must ensure that (1) multidisciplinary teams are created to perform comprehensive and credible sustainability evaluations; (2) problem structuring and model construction are as important as (if not more important) than the results (i.e. decision recommendations) themselves; (3) identification of the appropriate MCDA method depends on the problem at hand and not vice-versa; and (4) the credibility of the decision recommendations is subject to the preferences of the decision-makers. If these considerations are accounted for, the possibility of advancing nanotechnology on a sustainable path is very concrete and realistic

Multi-attribute value measurement and economic paradigms in environmental decision making

Bibliography: p. 219-228.The two environmental decision-making approaches of environmental economics (EE) valuation and multi-criteria decision analysis (MCDA) differ fundamentally in their underlying philosophies and approach; hence they are characterised as paradigms. The EE paradigm includes the idea that, if appropriate prices can be found and implemented for goods not normally traded on the market, then the market mechanism will efficiently distribute resources and decisions are therefore based on the concepts of individual willingness to pay and consumer sovereignty. That an efficient market is not necessarily equitable or sustainable has long been acknowledged, but EE adjustments are subject to theoretical and methodological problems. The MCDA paradigm is based on the idea that values and preferences should be examined and constructed through interaction between workshop participants and the analyst, given basic measurement theory axioms. Various EE and MCDA methods have been devised for measuring value in different contexts, some of which were applied, in the context of environmental (particularly water resources) management, in six action research case studies. The EE methods were contingent behaviour valuation, the contingent valuation method, conjoint analysis and the travel cost method. The MCDA method was a version of the simple multi-attribute rating technique (called SMARTx). In the SMARTx cases, applying a group-value sharing model during a series of workshops, stakeholders rated the effect of alternatives on a number of environmental, social and economic attributes directly or using value functions and gave weights to criteria. Indirect compensatory values of one criterion in terms of another were determined. In the EE cases, survey respondents were asked their travel costs, preference for multi-attribute profiles and willingness to pay for alternatives. Total and average willingness to pay for an amenity, its attributes or changes in environmental quality were determined. The practical and theoretical implications of applying the different methods were examined and compared in terms of four metacriteria: resonance with and validity within the prevailing political and decision-context, general validity and reliability, ability to include equity and sustainability criteria and practicality