| Abstract [eng] |
In practice, optimization problems are often multiple criteria. The criteria are usually contradictory, so the final decision depends on a decision maker. When the problem is solved interactively, the decision maker can change his/her preferences in decision process. Moreover, it is important to obtain solutions from the whole Pareto front. A decision support system adapted to the specific of the problem is essential for solving multiple criteria optimization problems interactively. The objects of research are multiple criteria optimization problems, interactive methods for solving these problems, interactive decision support systems, and application of parallel computing in decision support systems. Multiple criteria optimization methods are analyzed in the dissertation. The focus of attention is the methods for a uniform distribution of solutions on the Pareto front as well as the interactive methods. An interactive way for solving multicriteria optimization problems, which finds alternative solutions uniformly distributed on the Pareto front is proposed and investigated in this dissertation. An interactive decision support system which integrates the created interactive solving way, the decision process visualization and parallelization for multiple criteria optimization is developed. The solving strategies, when a multiple criteria optimization problem is solved interactively, using a computer cluster are developed and compared experimentally. The time required for a decision maker to learn to solve a multiple criteria optimization problem by the interactive decision support is investigated experimentally. |
