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November 10, 2026
Physicists Train AI to Optimise Particle Beams in Accelerators
Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science and the Budker Institute of Nuclear Physics at the Siberian Branch of the Russian Academy of Sciences have developed RLABC (Reinforcement Learning for Accelerator Beamline Control), a framework that uses reinforcement learning to identify optimal settings for a particle accelerator. In a computer simulation, RLABC optimised the accelerator's parameters to achieve a particle transmission rate of 70%. The study has been published in Computer Physics Communications.
November 9, 2026
'Organ-on-a-Chip Technology Could Eliminate the Need for Animal Testing'
The Laboratory of Molecular Physiology at the HSE Faculty of Biology and Biotechnology investigates how molecular regulators known as microRNAs control gene expression and contribute to the development of diseases, including cancer, viral and inflammatory conditions, and pregnancy complications. At HSE University, researchers develop organ-on-a-chip models: miniature devices containing living cells that mimic the functions of human organs, such as the placenta and intestines. These models help researchers understand how diseases develop and how drugs affect them. HSE News Service spoke with Evgeny Knyazev, Head of the Laboratory.
November 9, 2026
Flattened Terrain Models Underestimate Vehicle-to-Vehicle Communication Outages
Researchers at HSE MIEM have shown that widely used simulators of vehicle-to-vehicle communication significantly overestimate its reliability because they assume flat terrain. When terrain features, bridges, and tunnels are taken into account, the outage rate on a mountain serpentine road rises from 21% to 30%, on an overpass from 20% to 33%, and in a tunnel from 0% to 80%. The results have been published in Future Transportation.

 

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Optimization Problems in Graph Theory

Book 139. Springer, 2018.
Under the general editorship: B. Goldengorin

This book presents open optimization problems in graph theory and networks. Each chapter reflects developments in theory and applications based on Gregory Gutin’s fundamental contributions to advanced methods and techniques in combinatorial optimization. 

Researchers, students, and engineers in computer science, big data, applied mathematics, operations research, algorithm design, artificial intelligence, software engineering, data analysis, industrial and systems engineering will benefit from the state-of-the-art results presented in modern graph theory and its applications to the design of efficient algorithms for optimization problems. 

Topics covered in this work include:

·         Algorithmic aspects of problems with disjoint cycles in graphs

·         Graphs where maximal cliques and stable sets intersect

·         The maximum independent set problem with special classes

·         A general technique for heuristic algorithms for optimization problems

·         The network design problem with cut constraints

·         Algorithms for computing the frustration index of a signed graph

·         A heuristic approach for studying the patrol problem on a graph

·         Minimum possible sum and product of the proper connection number

·         Structural and algorithmic results on branchings in digraphs

·         Improved upper bounds for Korkel--Ghosh benchmark SPLP instances

Chapters
On graphs whose maximal cliques and stable sets intersect
Gurvich V., Andrade D. V., Boros E., , in: Optimization Problems in Graph TheoryBook 139.: Springer, 2018. P. 3–63.
We say that a graph G has the CIS-property and call it a CIS-graph if every maximal clique and every maximal stable set of G intersects. By definition, G is a CIS-graph if and only if the complementary graph \(\overline {G}\) is a CIS-graph. Let us substitute a vertex v of a graph G′ by a graph G″ and denote the obtained graph by G. It is also easy to ...
Added: October 10, 2018
Priority areas: mathematics
Language: English
DOI
Text on another site
Keywords: combinatorial optimizationapproximation algorithmsdirected graphsheuristic methodsdecision making problemstraveling salesman problemtransportation industriesdata Analyticsomputational complexity analysisgraph optimizationnetwork design problemdisjoint cycles in graphs
Optimization Problems in Graph Theory
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