Approximation and Online Algorithms

This thesis presents results of our research in the area of optimization problems with incomplete information-our research is focused on the online scheduling problems. Our research is based on the worst-case analysis of studied problems and algorithms; thus we use methods of the competitive analysis during our research. Althrough there are many "real-world" industrial and theoretical applications of the online scheduling problems there are still so many open problems with so simple description. Therefore it is important, interesting and also challenging to study the online scheduling problems and their simplified variants as well. In this thesis we have shown the following our results of our research on the online scheduling problems: A 1.58-competitive online algorithm for the problem of randomized scheduling of unit jobs on a single processor, where the jobs are arriving over time and the total weight of processed jobs ismaximized. A lower bound 1.172 on the competitive ratio for the problem of randomized scheduling of 2-uniform unit jobs on a single processor, where the jobs are arriving over time andthe totalweight of processed jobs is maximized. A lower bound 1.25 on the competitive ratio for the problem of randomized scheduling of s-uniform unit jobs on a single processor where s is tending to..