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Scheduling of tasks on moving executors is considered. It is formulated as the discrete optimization problem. The overview of solution algorithms is given. Approximate and AI-based algorithms are presented. In the approximate algorithm the solution algorithms for solving the classical scheduling problem and TSP are applied. Different versions of the evolutionary algorithm are also described. They comprise adaptation or learning of crossover and mutation probabilities. The comparison of the scheduling algorithms presented via computer simulation is given.
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Operational Program Digital Poland, 2014-2020, Measure 2.3: Digital accessibility and usefulness of public sector information; funds from the European Regional Development Fund and national co-financing from the state budget.
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