Manejando información incompleta en problemas de toma de decisiones en grupo en contexto difuso

Abstract

Decision making is on a thought and cognitive process of selecting a logical and best choice from the set of available options. This is a pervasive task in human beings every day routine. Indeed, we make choices ranging from quotidian elections, such as the type of coffee, to more complex and transcendentals selections, such as the best investment. Therefore the study of decision making mechanisms to obtain the best solution has attracted extensive research attention in very diverse areas ranging from Economy, Psychology and Sociology to Artificial Intelligence, and Engineering. When it comes to the case of a complex choices, in the majority of the occasions, the decision is made by a group of people, also known as group of experts. This kind of decision making processes involving more than one person is formally known as Group Decision Making, GDM. In this situation, even though experts, may have their own opinions and background approaching the problem from different perspectives, they share the common interest in reaching agreement on selecting the most suitable options.

The main aim of this dissertation lies in the study and development of new group decision making approaches under highly uncertainty environments with missing information.

When dealing with multiple experts in decision making situations, in this new demanding environments some specific research challenges arise.

In the following we briefly describe those challenges and explain how this dissertation aims to improve the state of the art of the current research efforts in these lines.