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  • Алгоритм ветвей и границ для задачи о формировании производственных ячеек
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News
April 30, 2026
HSE Researchers Compile Scientific Database for Studying Childrens Eating Habits
The database created at HSE University can serve as a foundation for studying children’s eating habits. This is outlined in the study ‘The Influence of Age, Gender, and Social-Role Factors on Children’s Compliance with Age-Based Nutritional Norms: An Experimental Study Using the Dish-I-Wish Web Application.’ The work has been carried out as part of the HSE Basic Research Programme and was presented at the XXVI April International Academic Conference named after Evgeny Yasin.
April 30, 2026
New Foresight Centre Study Identifies the Most Destructive Global Trends for Humankind
A team of researchers from the HSE International Research and Educational Foresight Centre has examined how global trends affect the quality of human life—from life expectancy to professional fulfilment. The findings of the study titled ‘Human Capital Transformation under the Influence of Global Trends’ were published in Foresight.
April 28, 2026
Scientists Develop Algorithm for Accurate Financial Time Series Forecasting
Researchers at the HSE Faculty of Computer Science benchmarked more than 200,000 model configurations for predicting financial asset prices and realised volatility, showing that performance can be improved by filtering out noise at specific frequencies in advance. This technique increased accuracy in 65% of cases. The authors also developed their own algorithm, which achieves accuracy comparable to that of the best models while requiring less computational power. The study has been published in Applied Soft Computing.

 

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Алгоритм ветвей и границ для задачи о формировании производственных ячеек

Программные продукты, системы и алгоритмы. 2017. № 4. С. 1–10.
Utkina I. E., Batsyn M. V.

The Cell Formation Problem (CFP) is an NP-hard optimization problem considered for cellular man- ufacturing systems. Because of its high computational complexity there have been developed a lot of heuristics and almost no exact algorithms for solving this problem. In this paper we suggest a branch- and-bound algorithm which provides exact solutions for the CFP with the grouping efficacy objective function. To linearize this fractional objective function we apply the Dinkelbach approach. Our algorithm finds optimal solutions for 24 of the 35 popular benchmark instances from literature and for the remaining instances it finds good solutions close to the best known. The difference in the grouping efficacy with the best known solutions is always less than 1.5%. 

Priority areas: IT and mathematics
Language: Russian
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Keywords: бикластеризацияBranch and Bound algorithmcell formation problemметод ветвей и границbiclusteringDinkelbach algorithmточное решение exact solutionФормирование производственных ячеекметод Динкельбаха
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