Doctor of Science,
Russian Academy of Sciences,
Moscow, Russia
Data Correcting and Tolerance Based Algorithms
Data Correcting and Tolerance Based Algorithms representing a unified approach to modeling and solving problems in Applied Combinatorial Optimization, e.g. Preemptive Single Machine Scheduling, Maximization (Minimization) of Submodular (Supermodular) Functions, Pseudo-Boolean Polynomials in Multidimensional Big Data Aggregation, Max-Clique, Max-Cut (including Quadratic Cost Partition), Capacitated Vehicle Routing in Cloud Computations applied to Virtual and Physical Resources, Facility Locations, Cell Formation in Industrial Engineering some of which might be found on amazon.com click
The aim of this program is to establish world wide competitive Mathematical Models, Algorithms, and Software with the purpose to solve computationally intractable benchmark instances