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

Système d'aide à la décision multicritère orienté Web pour la répartition des ressources des universités publiques brésiliennes

L'objectif principal de cette étude est de proposer un système d'aide à la décision multicritères orienté Web pour l'allocation interne des ressources dans les universités publiques brésiliennes afin de démontrer comment l'utilisation d'une méthode de décision multi-attributs appropriée pourrait améliorer la distribution d'un budget limité en utilisant une fonction de valeur additive combiné avec un système pour décentraliser la réalisation des tâches, afin d’augmenter la productivité des membres du groupe et pour améliorer la gestion des données en utilisant le Web. Ainsi, une université fédérale brésilienne a été choisie comme étalon afin d’avoir une application numérique du modèle multicritère développé. La disponibilité des données et la similitude avec un modèle général au Brésil nous a influencés pour ce choix. L'université analysée dans cette recherche à 21 unités administratives sectorielles (UAS) qui sont divisées par domaines, tels que les sciences humaines, les sciences biologiques, l'ingénierie, la faculté de médecine, etc., et chacune d'entre elles a des besoins budgétaires annuels. L'objectif est que l'application d'un modèle correct pour répartir le budget local entre ces unités puisse contribuer à la stratégie permanente de l'Université en matière d'allocation efficace et équitable des ressources. L'idée est que le système multicritère pourrait soutenir les décideurs, les parties prenantes qui participent au processus de décision et décentraliser la réalisation des tâches, puisque les SIAD orientés Web offrent des outils de recherche intelligents qui pourraient leur permettre de trouver et de gérer l'information rapidement et à peu de frais. En outre, il est important de souligner que le modèle présenté ici pourrait être étendu et utilisé par d'autres universités fédérales au Brésil ou dans d'autres pays, en adaptant les alternatives et les critères pour chaque cas spécifique. La principale préoccupation est de démontrer l'utilisation d'un DSS Web multicritères pour ce problème particulier.The allocation of scarce resources is a complex problem, especially when it comes to budget constraints. Thus, this work aims to propose a multicriteria web-based Decision Support System for resource allocation in the context of higher education organizations, more precisely, public universities that have budget constraints, such as Brazilian federal universities. To do so, a Brazilian federal university was chosen as an end-user to make a numerical application to validate the multicriteria model for resource allocation proposed and, afterward, a web-based DSS was developed. For the MCDM resource allocation model, an additive value function was considered to set the percentage of the total budget that every alternative should receive. The problem was seen as a special case of project portfolio selection problem because its approach is deemed to be appropriate for a resource allocation decision context. For the web-based DSS, the analysis was carried out by developing a DSS Database model to store and retrieve data, defining the user’s interface based on his detailed requirement analysis and using a web platform to transform the prototype into a web-based system. The results were achieved. The system provided a clear vision on how the resource allocation procedure works, the entire process became more transparent to the ones that are affected by it, to the decision makers and to the government, enabling them to take safer and reliable decisions, seeking to reduce uncertainties and to maximize their results. The multicriteria web-based DSS presented here could be extended and applied by other federal universities in Brazil or other countries, adapting the alternatives and criteria for each specific internal allocation model and to the DM needs

Multi-Criteria Decision Making in Complex Decision Environments

In the future, many decisions will either be fully automated or supported by autonomous system. Consequently, it is of high importance that we understand how to integrate human preferences correctly. This dissertation dives into the research field of multi-criteria decision making and investigates the satellite image acquisition scheduling problem and the unmanned aerial vehicle routing problem to further the research on a priori preference integration frameworks. The work will aid in the transition towards autonomous decision making in complex decision environments. A discussion on the future of pairwise and setwise preference articulation methods is also undertaken. "Simply put, a direct consequence of the improved decision-making methods is,that bad decisions more clearly will stand out as what they are - bad decisions.

SUP&R DSS: A sustainability-based decision support system for road pavements

Road pavement community members are increasingly becoming aware of the need to incorporating the principles of sustainable development into the sector. Policies are also going in this direction and as a consequence in the recent years researchers and practitioners are coming up with new materials, technologies and practices designed to reduce the negative impacts of their activities in the surroundings. Within this framework the road pavements sector is witnessing a paradigm shift towards the development of pavement technologies incorporating high-content of recycled materials, as well as best practices to decrease the overall carbon footprint. These are all promising solutions that to the most can sound as sustainable practices. However the whole road pavement community is still investigating methodologies and tools to define what actually sustainable means and thereby performing a sustainable decision-making. It is within this context that the need of a sustainability-based decision support system (DSS) that could help road pavement engineers at the design stage was identified and is here presented. The Sustainable Pavements & Railways DSS (SUP&R DSS) relies on a multi-criteria decision analysis (MCDA) method to rank the sustainability of alternatives. It applies life cycle-based approaches to quantify the values of a set of indicators purposely and methodologically selected to capture the cause- effect link between the general concepts of the three wellbeing dimensions of sustainability, i.e., environmental, economic and social, and the infrastructure construction and maintenance practice. Furthermore, the system allows selecting different weighting for the indicators but offers also a default set of values derived from a survey conducted with over 50 stakeholders in Europe and beyond. Together with the development, structure and features of the SUP&R DSS, this paper present its applicability by means of a case study aiming at identifying the most sustainable asphalt mixture for wearing courses. Several promising options for flexible road pavements were selected, ranging from low to hot temperature asphalt. The results show that a foamed warm mix asphalt mixture with a reclaimed asphalt pavement content of 50% is the most sustainable among the competing alternatives. Furthermore, a sensitivity analysis conducted to investigate the influence of the indicators weights, the parameters of the MCDA method and the long-term performance of the alternative asphalt mixtures on the stability of the ranking showed that its first position in the ranking remained unaffected

Integrated Frameworks for Effective Multi-criteria Decision Making in Reliability Centred Maintenance of Industrial Machines

No abstract availabl

Key challenges and meta-choices in designing and applying multi-criteria spatial decision support systems

There is an increasing use of multi-criteria spatial decision support systems in recent years for dealing with problems that have a spatial distribution of consequences. This growth might be explained by the widespread recognition that there are multiple and conflicting objectives to be considered in spatial planning (e.g. minimizing pollution to air, water and soil, increasing the acceptance of the projects, reducing implementation costs), by new requirements to consider societal values in the evaluation and to increase participation in decision processes, as well as by the crucial role that the spatial dimension plays in such problems. However, we argue in this paper that there are key challenges confronted by DSS designers who are developing such systems and by DSS practitioners who are employing them to support decision making. These challenges impose important meta-choices to designers and practitioners, which may lead to different contents of the evaluation model and to distinctive outcomes of the analysis. In this paper, we present and discuss these key challenges and the associated meta-choices. The contribution that we aim to provide to both researchers and practitioners can be summarized as follows: (i) an increased awareness about choices to be made in the design and implementation of these decision support systems; (ii) a better understanding about the available alternatives for each choice, based on recent developments in the literature; and (iii) a clearer appraisal about the inherent trade-offs between advantages and disadvantages of each alternative

Multicriteria Methodology for the NEEDS Project

This report begins with an overview of multicriteria analysis methods, and the basic principles of developing mathematical models for such analysis. An overview of various representation of user preferences is then presented, including methods based on pairwise comparisons of criteria and those based on scalarizing functions. This is followed by a summary of structures of criteria and alternatives. Next, basic properties of multi-criteria analysis are discussed, followed by a more detailed presentation of the similarities of and differences between the main methods based on scalarizing functions. This report concludes that existing methods do not best meet the needs of the NEEDS project, presents the reasons, and proposes a new methodology for development. Depending upon the development and testing of this new methodology, an existing method will also be chosen as a backup for comparative or alternate use