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Development of a multi-criteria intelligent decision system, to support large-scale group decision making in emergency situations

Fragkopoulos Dimitrios

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Summary

The decision-making process of groups, in corporation and organization, has been studied by many scientific fields, including the field of operational research combined with the development of intelligent systems.The scope of this thesis is to propose and apply a methodology for supporting large-scale group decision-making in emergency situations, where the group consists of decision makers from many different backgrounds, making the convergence under time pressure on a commonly accepted solution a challenge.For these reasons, the proposed methodology approaches the problem with multicriteria analysis methods, specifically incorporating the UTA and TOPSIS family of methods. Furthermore, datamining techniques and clustering/classification of data will be used, to support the extraction of big data from many sources, such as the web.The system will be developed using one of the latest versions of the python programming language. Furthermore, a graphical user interface will be added, to increase the ease of use and accessibility of such systems, for research and educational purposes.The system aims to achieve each goal, by increasing the amount of useful information exchanged by the decision makers, by informing them about each other’s preference model through an interactive feedback process. The final goal of this iterative process is to achieve a type of convergence of the decision makers preference, to find a satisfactory alternative of acceptance.

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