Optimalizační modely pro hodnocení efektivnosti a výkonnosti

General tools for the analysis of performance evaluation of a set of economic units usually consider variables (inputs and outputs) within one period. However, in practice of organisations are on-going concerns, and it is important to assess their productivity change over time in addition to the snap-shot assessments of efficiency in specific time periods. A number of methods have been proposed for this type of dynamic analysis, notably using data envelopment analysis (DEA) models, Malmquist indices, window analysis, and others. However, these methods still have certain shortcomings. The aim of this project is to develop models for evaluating performance which will be able not only to consider the past and current behaviour of the evaluated units, but also to predict their future developments. The project will also be interested in the construction of dynamic DEA network models and ranking of units under evaluation. Dynamic resource allocation based on the results of past periods will also be an important research task. Additionally, the project will involve working with large datasets, which have high computational time requirements. Therefore, the scientific team will employ metaheuristic algorithms to find sub-optimal but potentially optimal solutions. Algorithms combining standard DEA methodology and models from multiple criteria decision making theory will be proposed for the complete ranking of efficient units. The project will also address practical aspects, including the application and validation of the proposed models using real datasets in various economic sectors.