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Global equilibrium search algorithms for combinatorial optimization problems
Lecture Notes in Computer Science. 2012. Vol. 7492 LNCS. No. 2. P. 277–286.
Global Equilibrium Search (GES) is a meta-heuristic framework that shares similar ideas with the simulated annealing method. GES accumulates a compact set of information about the search space to generate promising initial solutions for the techniques that require a starting solution, such as the simple local search method. GES has been successful for many classic discrete optimization problems: the unconstrained quadratic programming problem, the maximum satisfiability problem, the max-cut problem, the multidimensional knapsack problem and the job-shop scheduling problem. GES provides state-of-the-art performance on all of these domains when compared to the current best known algorithms from the literature. GES algorithm can be naturally extended for parallel computing as it performs search simultaneously in distinct areas of the solution space. In this talk, we provide an overview of Global Equilibrium Search and discuss some successful applications.
Priority areas:
IT and mathematics
Language:
English
Piontkovski D., / Series arXiv "math". 2026.
A noncommutative projective variety is defined, following Artin and Zhang, by a graded coherent algebra 𝐴. The category of coherent sheaves is then the quotient qgr(𝐴) of the category of finitely presented graded modules by the subcategory of torsion modules. We consider the categorical and polynomial entropies of the Serre twist, that is, of the ...
Added: June 23, 2026
Piontkovski D., / Series arXiv "math". 2025.
If a symmetric multilinear algebra is weakly nil, then it is Engel. This result may be regarded as an infinite-dimensional analogue of the well-known Jacobian theorem, which states that if a polynomial mapping has a polynomial inverse, then its Jacobian matrix is invertible. This refines a theorem of Gerstenhaber and partially answers a question posed ...
Added: June 23, 2026
Shipilov F., Barnyakov A., Ivanov A. et al., / Series Physics "arxiv.org". 2026.
A fast simulation of the detector response is a vital task in high-energy physics (HEP). Traditional Monte-Carlo methods form the backbone of modern particle physics simulation software but are computationally expensive. We present a machine-learning-based approach to fast simulation of the Focusing Aerogel Ring Imaging Cherenkov (FARICH) detector response. Given a particle track and momentum, ...
Added: May 19, 2026
Derkacheva A., Sakirkina M., Kraev G. et al., /. 2026.
Comprehensive data on natural hazards and their consequences are crucial for effective for risk assessment, adaptation planning, and emergency response. However, many countries face challenges with fragmented, inconsistent, and inaccessible data, particularly regarding local-scale events. To address this data gap in Russia, we developed an end-to-end processing pipeline that scrapes news from various online sources, ...
Added: April 28, 2026
Pilé I., Deng Y., Shchur L., / Series arXiv "math". 2026. No. 2604.10254.
We investigate the spatial overlap of successive spin configurations in Markov chain Monte Carlo simulations using the local Metropolis algorithm and the Svendsen-Wang and Wolff cluster algorithms. We examine the dynamics of these algorithms for two models in different universality classes: the Ising model and the Potts model with three components. The overlap of two ...
Added: April 20, 2026
Gabdullin N., Androsov I., / Series Computer Science "arxiv.org". 2026.
Label prediction in neural networks (NNs) has O(n) complexity proportional to the number of classes. This holds true for classification using fully connected layers and cosine similarity with some set of class prototypes. In this paper we show that if NN latent space (LS) geometry is known and possesses specific properties, label prediction complexity can ...
Added: April 2, 2026
Sorokin K., Beketov M., Онучин А. et al., / arxiv.org. Серия cs.SI "Social and Information Networks ". 2025.
Community detection in complex networks is a fundamental problem, open to new approaches in various scientific settings. We introduce a novel community detection method, based on Ricci flow on graphs. Our technique iteratively updates edge weights (their metric lengths) according to their (combinatorial) Foster version of Ricci curvature computed from effective resistance distance between the ...
Added: January 15, 2026
Petrovanov I., Sergeev A., / Series Computer Science "arxiv.org". 2025. No. 2512.18332.
Transport coding reduces message delay in packet-switched networks by introducing controlled redundancy at the transport layer: original packets are encoded into coded packets, and the message is reconstructed after the first successful deliveries, effectively shifting latency from the maximum packet delay to the -th order statistic. We present a concise, reproducible discrete-event implementation of transport coding in OMNeT++, including ...
Added: December 24, 2025
Hessian-based lightweight neural network for brain vessel segmentation on a minimal training dataset
Меньшиков И. А., Бернадотт А. К., Elvimov N. S., / Series arXie "Statistical mechanics". 2025.
Accurate segmentation of blood vessels in brain magnetic resonance angiography (MRA) is essential for successful surgical procedures, such as aneurysm repair or bypass surgery. Currently, annotation is primarily performed through manual segmentation or classical methods, such as the Frangi filter, which often lack sufficient accuracy. Neural networks have emerged as powerful tools for medical image ...
Added: December 1, 2025
Springer Publishing Company, 2025.
The three-volume set LNCS 14476-14478 constitutes the post conference proceedings of the 4th International Conference on Numerical Computations: Theory and Algorithms, NUMTA 2023, held in Pizzo Calabro, Italy, during June 14–20, 2023.
The 45 full papers presented in this book together with 60 short papers were carefully reviewed and selected from 170 submissions.
The papers focus on ...
Added: November 23, 2025
Rubchinskiy A., Chubarova D., / Series WP7 "Математические методы анализа решений в экономике, бизнесе и политике". 2025. No. WP7/2025/01.
The article examines one of the most famous examples of socio-economic systems, characterized by significant uncertainty – the S&P-500 stock market, where shares of 500 largest US companies are traded. No assumptions are made about the probabilistic characteristics of the stock market. A flexible algorithm for daily trading has been developed, based on both known fixed data ...
Added: November 9, 2025
Кочкаров А. А., Yatskin D., Рахманов О. А., Известия ЮФУ. Технические науки 2016 № 2 С. 158–168
The problem of limited space monitoring is formulated. The connection between the monitoring space and the detection of objects in this space sets up. After introducing some assumptions we conclude the necessity of solving the covering set (connected space) problem. The presence of obstacles in the monitoring area is the characteristic feature of the problem. ...
Added: March 7, 2025
Морозов Н. Ю., Гришин Е. М., Правдивец Н. А. et al., Управление большими системами: сборник трудов 2022 № 99 С. 135–156
В связи с ростом объема мультимодальных перевозок ОАО «РЖД» требуется более эффективное использование имеющихся ресурсов. В наши дни наиболее востребованной разновидностью международного грузооборота является доставка морским транспортом с последующей перегрузкой на железную дорогу для доставки до пункта назначения на материке. В настоящей статье предлагается комплексная математическая модель, включающая две подзадачи: задачу назначения причалов (BAP) и ...
Added: December 7, 2022
Grishin E., Pravdivets N., Morozov N. et al., IFAC-PapersOnLine 2022 Vol. 55 No. 10 P. 2557–2562
Sea transport holds the first place in the total number of freight shipments of international transportation. Rail transport takes more than 87% of domestic freight traffic and is increasing annually. In particular, Russian Railways deals with scheduling in international multimodal transport. Sea port-railway transshipment points have a key role in the realization of such transportation. ...
Added: December 7, 2022
Smirnov S., Voloshinov V., O.V. Sukhoroslov, , in: Proceedings of the 9th International Conference "Distributed Computing and Grid Technologies in Science and Education" (GRID'2021), Dubna, Russia, July 5-9, 2021.: CEUR Workshop Proceedings, 2021. P. 413–417.
ParaSCIP is rather advanced open-source solver for discrete and global optimization problems. This solver is distinguished by that it can run on distributed memory systems and use up to 80,000 cores, solving open problems from the MIPLIB test libraries. Earlier, using this solver, we confirmed the conjecture on optimal packing of nine congruent circles on ...
Added: October 30, 2022
Du J., Wen Y., Wang L. et al., Annals of Mathematics and Artificial Intelligence 2023 Vol. 97 P. 117–216
Human Learning Optimization (HLO) is a simple yet efficient binary meta-heuristic, in
which three learning operators, i.e. the random learning operator (RLO), individual
learning operator (ILO) and social learning operator (SLO), are developed to mimic
human learning mechanisms to solve optimization problems. Among these three operators,
RLO directly influences the exploration and exploitation abilities of HLO, and
therefore its control ...
Added: May 26, 2022
Ignatov A., Posypkin M., , in: Optimization and Applications: 12th International Conference, OPTIMA 2021, Petrovac, Montenegro, September 27 – October 1, 2021, Proceedings.: Switzerland: Springer, 2021. P. 336–350.
Restoration of the 3D structure of a protein from the sequence of its amino acids (“folding”) is one of the most important and challenging problems in computational biology. The most accurate methods require enormous computational resources due to the large number of variables determining a protein’s shape. Coarse-grained models combining several protein atoms into one ...
Added: May 20, 2022
Zhang P., Du J., Wang L. et al., Applied Soft Computing Journal 2022 Vol. 122 Article 108816
Human Learning Optimization (HLO) is a simple yet powerful meta-heuristic developed based on a simplified human learning model. Many cognitive activities of humans contain an element of reasoning, and with reasoning, humans can gain deeper information on problems to boost learning performance. Inspired by this fact, this paper proposes a novel human learning optimization algorithm ...
Added: April 11, 2022
Gadetsky A., Struminsky K., Robinson C. et al., , in: Thirty-Fourth AAAI Conference on Artificial IntelligenceVol. 34.: AAAI Press, 2020. P. 10126–10135.
Added: October 11, 2020
Cham: Springer, 2020.
This book constitutes the proceedings of the 19th International Conference on Mathematical Optimization Theory and Operations Research, MOTOR 2020, held in Novosibirsk, Russia, in July 2020. The 31 full papers presented in this volume were carefully reviewed and selected from 102 submissions. The papers are grouped in these topical sections: discrete optimization; mathematical programming; game ...
Added: September 2, 2020
Omelchenko A., Malozemov V. N., Journal of Industrial and Management Optimization 2006 Vol. 2 No. 1 P. 55–62
A two-dimensional discrete optimal control problem is considered. In this problem it is required that the first component admits the given value and the second component attains the largest value at the last step. The explicit solution of this problem is obtained under some assumptions. ...
Added: September 11, 2018
Kohli P., Osokin A., Jegelka S., , in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2013).: Portland: IEEE, 2013. P. 1971–1978.
We discuss a model for image segmentation that is able to overcome the short-boundary bias observed in standard pairwise random field based approaches. To wit, we show that a random field with multi-layered hidden units can encode boundary preserving higher order potentials such as the ones used in the cooperative cuts model of [11] while ...
Added: October 19, 2017
D. Derkach, N. Kazeev, R Neychev et al., Journal of Physics: Conference Series 2017 Vol. 898 No. 6 P. 1–6
The LHCb experiment stores around 1011 collision events per year. A typical physics analysis deals with a final sample of up to 107 events. Event preselection algorithms (lines) are used for data reduction. Since the data are stored in a format that requires sequential access, the lines are grouped into several output file streams, in ...
Added: October 10, 2017
Turkensteen M., Malyshev D., Goldengorin B. I. et al., Journal of Global Optimization 2017 Vol. 68 No. 3 P. 601–622
The tolerance of an element of a combinatorial optimization problem with respect to its optimal solution is the maximum change of the cost of the element while preserving the optimality of the given optimal solution and keeping all other input data unchanged. Tolerances play an important role in the design of exact and approximation algorithms, ...
Added: December 10, 2016