Boolean functions and their applications in machine learning: from logical rules to explicable artificial intelligence
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Automated scheduling is an applied task of discrete optimization, where graph models and combinatorial algorithms directly affect the quality of educational solutions. The article considers the schedule as a combinatorial optimization problem: from constructing a conflict graph and reducing it to coloring to hybrid schemes combining mathematical programming (MIP), SAT/SMT approaches and evolutionary methods. Special attention is paid to modern open data and tools: ITC 2019 instances (UniTime) and libraries for real implementations. The results of Russian research demonstrating the effectivenes...