Solution of the problem of optimal task distribution by the method of dynamic programming with parallel computing

The aim of the study is to construct a parallel algorithm for solving a bottleneck (minmax) problem connected with partitioning a finite set of tasks between a finite number of agents. We describe the algorithm of finding an optimal partition of tasks through dynamic programming with a parallel computation of the Bellman function and provide a computational complexity estimate for the two algorithms (with and without the parallel construction). The algorithm was implemented for the Uran supercomputer, and a computational experiment was conducted; computation time was measured for the serial algorithm and for the parallel one on varying numbers of processor cores.