Russian
XXIII International Conference Mathematical Optimization Theory and Operation Research
XXIII International Conference Mathematical Optimization Theory and Operations Research MOTOR-2024 Omsk Russia, June 30 - July 06, 2024

 News
10.04.2024. Lists of articles for LNCS and CCIS
Dear Colleagues. Lists of accepted articles for the first volume (LNCS) and recommended articles for the second volume (CCIS) are published on the website.
 
15.03.2024. Change of deadlines for the notification of papers acceptance to proceedings volumes
Due to extension of submission deadline, the notification of papers acceptance to proceedings volumes is delayed till March, 31, 2024.
 
11.02.2024. Change of deadlines
The deadline for submission of papers and abstracts is extended to February, 29, 2024.
 
4.02.2024. Change of deadlines
The deadline for submission of papers and abstracts is extended to February, 19, 2024.
 
17.01.2024. EquinOCS system
Submission of abstracts and papers for conference proceedings is open via EquinOCS system: https://equinocs.springernature.com/service/MOTOR2024.
 
16.01.2024. Decision to publish in LNCS and CCIS Springer Nature
It has been decided that two volumes of conference proceedings will be published in LNCS and CCIS series of Springer Nature as in the previous editions of MOTOR conference.
 
11.01.2024. Extension of deadlines for submitting abstracts
The deadline for abstracts submission is moved to February, 5, 2024. The link to the submission system will be provided here as soon as it will become available.
 
18.12.2023. Conference website was opened
Conference website was created.
 
 Topics
  • Mathematical programming
  • Discrete optimization
  • Computational complexity and approximation algorithms
  • Metaheuristics and local search methods
  • Game theory
  • Optimization in machine learning and data analysis
  • Parallel computations to speed up the solution of optimization problems
  • Applications in operations research: scheduling, routing, facility location, packing and cutting, manufacturing systems, etc.
 Program Committee
Program committee chairs
  • Anton Eremeev, Dostoevsky Omsk State University, Omsk; Novosibirsk State University, Novosibirsk (Russia)
  • Yuri Kochetov, Sobolev Institute of Mathematics, Novosibirsk (Russia)
  • Vladimir Mazalov, Institute of Applied Mathematical Research, Karelia Research Center of RAS, Petrozavodsk (Russia)
  • Mikhail Khachay, Krasovsky Institute of Mathematics and Mechanics, Ekaterinburg (Russia)
  • Panos Pardalos, University of Florida, Gainesville (USA); HSE, Nizhny Novgorod (Russia)
Program committee
  1. Aida-Zade K. prof., dr., corresponding member of NAS of Azerbaijan, Institute of Control Systems, Baku, Azerbaijan
  2. Antipin A., prof., dr., FRC CSC RAS, Russia
  3. Bagirov A., prof., dr., Federation University Australia, Australia
  4. Battaia O., prof., dr., KEDGE Business School, Bordeaux, France
  5. van Bevern R., dr., Novosibirsk State University, Novosibirsk, Russia
  6. Beresnev V., prof., dr., Sobolev Institute of Mathematics SB RAS, Novosibirsk, Russia
  7. Bolotashvili G., prof., dr., Georgian Technical University, Georgia
  8. Bushenkov V., prof., dr., University of Evora, Portugal
  9. Buzdalov M. dr., Aberystwyth University, UK
  10. Bykadorov I. docent, dr., Sobolev Institute of Mathematics SB RAS, Novosibirsk, Russia
  11. Vasilyev I., prof., dr., Matrosov Institute for System Dynamics & Control Theory SB RAS, Russia
  12. Vasin A. prof., dr., Lomonosov Moscow State University, Russia
  13. Gao H., prof., dr., Qingdao University, China
  14. Gasnikov A., prof., dr, Innopolis, Kazan, Russia
  15. Gimadi E., prof., dr., Sobolev Institute of Mathematics SB RAS, Novosibirsk, Russia
  16. Gornov A. dr., Matrosov Institute for System Dynamics and Control Theory, Russia
  17. Gurevsky E., dr., University of Nantes, Nantes, France
  18. Davidovic T., prof., dr., Mathematical Institute SASA, Belgrade, Serbia
  19. Dolgui A., prof, dr., IMT Atlantique, Nantes, France
  20. Erzin A., prof., dr., Sobolev Institute of Mathematics SB RAS, Novosibirsk, Russia
  21. Zolotykh N.Yu., prof., dr., Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia
  22. Kazakov A., prof., dr., Matrosov Institute for System Dynamics and Control Theory SB RAS, Irkutsk, Russia
  23. Kalyagin V., prof., dr., Higer School of Economics, Nizhny Novgorod, Russia
  24. Kartak V., prof., dr., State Aviation Technical University, Ufa, Russia
  25. Kibzun A. prof., dr., Moscow Aviation Institute, Russia
  26. Qian Ch. prof., dr., Nanjing University, China
  27. Kvasov D., DIMES, University of Calabria, Italy
  28. Kovalyov M., prof., dr., United Institute of Informatics Problems NASB, Minsk, Belarus
  29. Kong L., prof., dr., Beijing Jiaotong University, China
  30. Konnov I., prof., dr., KFU, Kazan, Russia
  31. Kononov A., prof., dr., Sobolev Institute of Mathematics SB RAS, Novosibirsk, Russia
  32. Lazarev A. prof., dr., ICS RAS, Moscow, Russia
  33. Lin B., prof., dr., National Yang Ming Chiao Tung University, Hsinchu, Taiwan
  34. Maniezzo V., prof., dr., University of Bologna, Cesena, Italy
  35. Nurminski E., prof., dr., Far Eastern Federal University, Vladivostok, Russia
  36. Petrosyan L.. prof., dr., SPBU, Saint-Petersburg, Russia
  37. Popov L. prof., dr., Krasovsky Institute of Mathematics and Mechanics, Russia
  38. Posypkin M. prof., dr., corresponding member of RAS, FRC CSC RAS, Russia
  39. Pyatkin A. prof., dr. Sobolev Institute of Mathematics, Novosibirsk, Russia
  40. Raha S., prof., dr., Indian Institute of Science, Bengaluru, India
  41. Rettieva A.N., dr., Institute of Applied Mathematical Research, Karelia Research Center of RAS, Petrozavodsk, Russia
  42. Semenkin E. prof., dr., Reshetnev University, Krasnoyarsk, Russia
  43. Sergeyev Ya. prof., dr. University of Calabria, Italy
  44. Sifaleras A., prof., dr., University of Macedonia, Greece
  45. Sleptchenko A. prof., dr., Khalifa University, UAE
  46. Strekalovsky A., prof., dr., Matrosov Institute for System Dynamics and Control Theory SB RAS, Irkutsk, Russia
  47. Todosijevic, R. prof., dr., UPHF, France
  48. Tseveendorj I., prof., dr., Universite de Versailles-Saint Quentin en Yvelines, Versailles, France
  49. Khamisov O. prof., dr., Matrosov Institute for System Dynamics and Control Theory, Russia
  50. Tsoy Y., dr., Ailys, Seoul, Republic of Korea
  51. Chen X., prof., dr., Institute of Applied Mathematics, Chinese Academy of Sciences, Beijing, China
  52. Cheng, Y. prof., dr., Suzhou University of Science and Technology, China
  53. Shananin A., prof., dr., academician of RAS, MIPT, Moscow, Russia
  54. Jacimovic M., prof., dr., University of Montenegro, Montenegro
  55. Yao X. prof., dr., Southern University of Science and Technology, China
 Important Dates
  • Abstracts submission: January, 15, 2024 February, 5, 2024 February, 19, 2024 February, 29, 2024.
  • Papers submission: February, 5, 2024 February, 19, 2024 February, 29, 2024.
  • Notification of acceptance of talks: March, 15, 2024.
  • Notification of acceptance of papers to proceedings: until April, 3, 2024.
  • Conference dates: June 30 - July 06, 2024.
 Keynote speakers
Prof. Xujin Chen
Institute of Applied Mathematics, Chinese Academy of Sciences, Beijing, China
Undirected Networks Immune to the Informational Braess's Paradox
The Informational Braess's paradox exposes a counterintuitive phenomenon that disclosing additional road segments to some selfish travelers results in increased travel times for these individuals. This paradox expands upon the classic Braess's Paradox by relaxing the assumption that all travelers possess identical and complete information about the network. In this presentation, we explore structual conditions that prevent the informational Braess paradox in undirected networks.
Prof. Rentsen Enkhbat
Business school of National University of Mongolia, Ulaanbaatar, Mongolia
Recent Advances in Game Theory
The title will be announced later.
Prof. Nikolai N. Guschinsky
Belarus, Minsk
Models and methods for optimization electric public transport systems
Information will be announced later.
Prof. Roland Hildebrand
Moscow Institute of Physics and Technology, Dolgoprudny, Russia
Tuning methods for minimization of self-concordant functions with optimal control
In the last decade the usage of optimization methods for performance estimation and tuning of other optimization methods has became fashionable. For instance, semi-definite programming allows to analyze the behaviour of accelerated gradient descent methods at minimizing functions of different regularity. Detecting the worst-case performance with respect to the minimized function and maximizing this performance with respect to the parameters of the method allows to obtain the best parameter set.
Here we show how to perform a similar analysis of the Newton method when minimizing self-concordant functions. This task arises as a subproblem in more complex structured convex optimization problems such as semi-definite programming inside path-following methods. The appropriate framework for optimizing the parameters, in particular, the step length and the search direction, is optimal control theory. We present a general technique to use the Pontryagin maximum principle in the analysis of the Newton step on a self-concordant function and specialize it in several case studies.
The talk in part presents joint work with Anastasia Ivanova.
Prof. Elena V. Konstantinova
China Three Gorges University, Yichang, China & Sobolev Institute of Mathematics, Novosibirsk, Russia
Recent progress in domination theory
In this talk, some recent results in domination theory are presented. In 2020, T.W. Haynes et al. introduced coalitions and coalition partitions based on dominating sets in graphs as a graph-theoretical model to describe political coalitions. The authors have been studied the property of this concept and suggested a list of open problems. In particular, it was suggested to study connected coalitions based on connected dominating sets. In this talk we focus on studying connected coalitions and their partitions in graphs with emphasising to polynomial-time algorithms determining whether the connected coalition number of a graph G of order n is either n or n-1. The talk is based on joint works with S. Alikhani, D. Bakhshesh, and H. Golmohammadi.
Prof. Panos M. Pardalos
University of Florida, Gainesville, USA; HSE, Nizhny Novgorod, Russia
AI and Optimization for a Sustainable Future

Panos M. Pardalos, University of Florida
www.ie.ufl.edu/pardalos
https://nnov.hse.ru/en/latna/

Advances in AI tools are progressing rapidly and demonstrating the potential to transform our lives. The spectacular AI tools rely in part on their sophisticated mathematical underpinnings (e.g. optimization techniques and operations research tools), even though this crucial aspect is often downplayed.

In this lecture, we will discuss progress from our perspective in the field of AI and its applications in Energy systems and Sustainability.

Prof. Alexander A. Shananin, academician of RAS
Moscow Institute of Physics and Technology, Moscow, Russia
Mathematical modeling of the consumer loan market in Russia (joint talk with N.V. Trusov)
In this talk we present the mathematical description of the economic behavior of a rational household in consumer loan market. The modeling of the economic behavior of households is based on the concept of a rational representative economic agent and arises to F. Ramsey. The model is formalized as an optimal control problem on a finite time horizon. The household maximizes discounted consumption with constant risk aversion, managing the dynamics of its expenditures depending on the current parameters of the economic situation and the behavioral characteristics of the household itself. We consider an imperfect market when the interest rate on loans differs from the interest rate on deposits. The difference in interest rates on loans and deposits leads to non-smoothness of the right-hand side of the differential equation for the phase variable. This motivates to use the Pontryagin maximum principle in the form of F. Clark. Applying it, we obtain an area where the household does not interact with the banking system, the special regimes arise. If we tend the time horizon of an optimal control problem to infinity, it is possible to construct a synthesis. The synthesis allows us to determine an optimal control depending on the current value of the phase variable and the parameters of the economic situation. It depends on current interest rates and on the behavioral characteristics of a representative household. We develop and investigate a new model for the formation of interest rates on consumer loans based on an analysis of commercial interests and the logic of behavior of commercial banks. The model assumes that the borrowers’ incomes are described by a geometric Brownian motion. The commercial banks assess the default risk of borrowers. According to the Feynman–Kac formula, the assessment is reduced to solving a boundary value problem for partial differential equations. An analytical solution to this problem is constructed. It is possible to reduce the solution of the boundary value problem to the Cauchy problem for the heat equation with an external source and obtain a risk assessment in analytical form with a help of the Abel equation. The models of economic behavior of households in the consumer loan market and behavior of commercial banks are identified based on Russian statistics. A specialized software has been developed to analyze the demand for consumer credit. With its help, the problems of the consumer lending market in Russia are analyzed.
Prof. Zaiwen Wen
Peking University, China
Exploring the Learning-based Optimization Algorithms

Abstract: The recent revolutionary progress of artificial intelligence has brought significant challenges and opportunities to mathematical optimization. In this talk, we briefly discuss two examples on the integration of data, models, and algorithms for the development of optimization algorithms: ODE-based learning to optimize and learning-based optimization paradigms for solving integer programming. We will also report a few interesting perspectives on formalization and automated theorem proving, highlighting their potential impact and relevance in contemporary mathematical optimization.

Bio: Wen Zaiwen, Professor at Peking University. He mainly studies optimization algorithms and theory and their applications in machine learning. He was awarded the China Youth Science and Technology Award in 2016 and Beijing Outstanding Youth Zhongguancun Award in 2020. He was funded by the National Ten Thousand Talents Program for Science and Technology Innovation. He is an associate editor of “Journal of Scientific Computing”, "Communications in Mathematics and Statistics", "Journal of the Operations Research Society of China", "Journal of Computational Mathematics" and a technical editor of "Mathematical Programming Computation".

Prof. Wenwu Yu
Southeast University, China
"Distributed Optimization +" in Networks: A New Framework

Distributed optimization is solved by the mutual collaboration among a group of agents, which arises in various domains such as machine learning, resource allocation, location in sensor networks and so on. In this talk, we introduce two kinds of distributed optimization problems: (i) the agents share a common decision variable and local constraints; (ii) the agents have their individual decision variables but that are coupled by global constraints.

This talk comprehensively introduce the origin of distributed optimization, classical works as well as recent advances. In addition, based on reinforcement learning, shortest path planning, and mixed integer programming, we build the distributed optimization framework of distributed optimization, and also discuss their applications. Finally, we make a summary with future works for distributed optimization.

 Tutorials
Yury Kochetov
Black box optimization for business applications
The black-box optimization models are characterized by lack of analytical forms for the constraints and the objectives of the problem. In the black-box methods, we need efficiently integrate known analytical part with explicitly unknown correlations obtained from the business simulation models. The direct use of classical global optimization methods is prohibitive due to the lack of exact mathematical expressions. We cannot calculate the derivatives or sub-gradients. Moreover, the computational cost is high due to the simulations. Hence, we have to use the problem specific methods to optimize such black-box systems efficiently. Important applications stem from various disciplines: multi-echelon inventory systems, chemical and mechanical engineering, financial management, network topology design, and others. In this talk, we will discuss some directions in this area and theoretical bounds for global optimization methods. Successful cases for real-world applications will be presented.
Pavel Borisovsky
Application of GPU computing to solving discrete optimization problems
Parallel computing on graphic processors (GPUs) is getting more and more popular. Since NVIDIA released the CUDA development tool, it has become convenient to use GPUs for general-purpose computing and not just for graphics display tasks. A feature of a GPU is the presence of a large (hundreds and thousands) number of cores, which allows to significantly speed up the calculation, but requires to design special parallel algorithms. While the development of traditional processors (CPUs) has recently slowed down, the characteristics of the GPU (number of cores, memory size, power consumption, and cost) are improving rapidly. In this tutorial, we will learn the basics of GPU computing in CUDA and OpenCL and briefly review the pros and cons of using GPUs in various discrete optimization algorithms.
 Conference Proceedings

Authors have the opportunity to submit their papers reporting on novel results that are not published or submitted simultaneously to any journal or another conference with refereed proceedings. Papers should be prepared in the Springer LNCS Format, can have 12-15 pages, and submitted in PDF. Pease, follow the official Springer authors guidelines. Articles submitted to journals or other peer-reviewed conferences will NOT BE accepted for consideration.

It has been decided that two volumes of conference proceedings will be published in LNCS and CCIS series of Springer Nature as in the previous editions of MOTOR conference.

Submission of abstracts and papers for conference proceedings is made via EquinOCS system: https://equinocs.springernature.com/service/MOTOR2024

After uploading a paper, authors from Russian organizations, are requested to send a copy of conclusion of the expert commission on the possibility of open publication of the paper to the email of the organizing committee (motor24@ofim.oscsbras.ru).

It is required that all contributing conference paper authors of MOTOR'2024 adhere to the Code of Conduct: (https://www.springernature.com/gp/authors/book-authors-code-of-conduct).

Volume 1: Lecture Notes in Computer Science

5 Yuskov, Kulachenko, Melnikov, Kochetov Stadium antennas deployment optimization
10 Popov How to use barriers and symmetric regularization of Lagrange function in analysis of improper nonlinear programming problems
13 Chirkova Potential Game in General Transport Network with Symmetric Externalities
19 Orlov On a Global Search in Bilevel Optimization Problems with a Bimatrix Game at the Lower Level
24 Lavlinskii, Panin, Plyasunov, Zyryanov Production and infrastructure construction in a resource region: a comparative analysis of mechanisms for forming a consortium of subsoil users
45 Nikolaev On 1-skeleton of the cut polytopes
48 Rentsen Recent Advances in Game Theory
49 Mikhailova One optimization problem induced by the segregation problem for the sum of quasiperiodic sequences
50 Rudakov, Ogorodnikov, Khachay Branching algorithms for the Reliable Production Process Design Problem
52 Gabidullina Assessing the Perron-Frobenius Root of Symmetric Positive Semidefinite Matrices by the Adaptive Steepest Descent Method
54 Kolnogorov UCB Strategies in a Gaussian Two-Armed Bandit Problem
63 Ilev, Il'ev Сlustering complexity and an approximation algorithm for a version of the Cluster Editing problem
65 Gong, Huang, Huang, Wang, Wang, Xiao, Yan, Yang A Unified Framework of Multi-Stage Multi-Winner Voting: An Axiomatic Exploration
74 Vasin, Grigoreva On the optimal management of energy storage
76 Servakh, Malakh Thе problem of planning investment projects with lending
92 Zhou, Mazalov Dynamic Stability of Coalition Structures in Network-Based Pollution Control Games
95 Quliyev, Aida-zade Automated and Automatic Systems of Management of an Optimization Programs Package for Decisions Making
97 Zhao, Parilina Network structure properties and opinion dynamics in two-layer networks with hypocrisy
98 Solodkin, Chezhegov, Nazykov, Beznosikov, Gasnikov Accelerated Stochastic Gradient Method with Applications to Consensus Problem in Markov- Varying Networks
100 Davydov Tabu Search for a service zone clustering problem
104 Huang, Hu, Yue, Liu, Liang Decision Analysis of Military Supply Chain Based on Stackelberg Game Model
115 Kharchenko, Kononov A Learning-Augmented Algorithm for the Parking Permit Problem with Three Permit Types
133 Turnaev, Panin Stochastic Greedy Algorithms for a Temporal Bin Packing Problem with Placement Groups
141 Kalyagin, Kostylev Robustness of Graphical Lasso Optimization Algorithm for Learning a Graphical Model
145 Trusov, Shananin Mathematical modeling of the interest rates formation on consumer loans in Russia
148 Petrosyan, Pankratova Differential Network Games with Different Type of Players Behavior
152 Yarmoshik, Persiianov On the Application of Saddle-Point Methods for Combined Equilibrium Transportation Models
153 Panin, Borisovsky, Eremeev, Sakhno Temporal Bin Packing Problems with Placement Constraints: MIP-Models and Complexity
155 Sevostyanov Filtering Correction for Robotic Arms Multipurpose Regulators
164 Vasilyev, Ushakov, Arkhipov, Davydov, Muftahov, Lavrentyeva Fast heuristics for a staff scheduling problem with time interval demand coverage

Volume 2: Communications in Computer and Information Science

2 Erzin, Anikeev Energy-efficient regular strip covering with fixed-size identical sectors
4 Erzin, Shadrina Optimal placement of mobile sensors for distance-constrained line routing problem
11 Shperling, Kochetov Fitness function based algorithm for the irregular 2D bin packing problem
21 Khandeev, Neshchadim Pseudo-polynomial algorithms for some problems of searching for the largest subsets
28 Davydov Akentev Greedy algorithms for the temporal bin packing problem with failure domain
29 Zabudsky Maximin and Maxisum Network Location Problems with Various Metrics and Minimum Distance Constraints
30 Mazalov, Ivashko Optimal Stopping Strategies in Gambler's Ruin Game
35 Zakharova, Zakharov Methods for Solving Large-Scale Problems of Customer Order Scheduling
36 Hashimov, Aida-zade Optimization of the movement of measurement points in one problem of synthesis of temperature control of a furnace for heating the rods
37 Panasenko Approximation Scheme for a Sequence Weighted 2-Clustering with a Fixed Center of One Cluster
55 Yarullin, Zabotin, Shulgina A Relaxed Cutting Method for the Convex Programming Problem
57 Akhmatshin, Kazakovtsev Mini-batch K-means++ clustering initialization
62 Marakulin Differential information economies: REE-equilibrium under contract based approach
80 Ershov, Voroshilov UCB Strategy For Batch Data Processing On An Unknown Horizon
88 Mu, Guo, Sun A Fast Algorithm for Submodular Maximization with a Matroid Constraint
99 Vasilyev, Gruzdeva, Barkova, Boyarkin, Iakubovskii On Active-Set Methods for Quadratic Problems with Positive Semidefinite Matrices
102 Buchinskiy, Kotov, Treier On generic-case complexity and NP-completeness of the problem of solving tropical polynomial systems of equations
103 Tang, Li, Diao Some Combinatorial Algorithms on the Edge Dominating Number of Hypergraphs with Minimum Degree
106 Sorokovikov, Gornov, Zarodnyuk Numerical Investigation of the Swarm Intelligence Algorithm Obtained Using ChatGPT for Univariate Global Optimization
127 Alkousa, Stonyakin, Abdo, Alcheikh Optimal Convergence Rate for Mirror Descent Methods with Special Time-Varying Step Sizes Rules
131 Marciano, Guarracino, Bernhardt Improved Credit Scoring model with Hyperparameter Optimization
135 Kaidash Super Domination Polynomial of a Graph
136 Vasilev, Khamisov, Vasilev Short-Term Voltage Instability Identification: A Combined Approach of Maximum Lyapunov Exponent and K-Means Clustering
151 Uskov, Kotezhekova A Real-World Parcel Routing Problem: MIP Formulation and Heuristic
156 Stepanov, Musatov Migrational Stability of Plane Tilings
158 Savchuk, Stonyakin, Puchinin, Alkousa, Gasnikov First-Order Methods for Variational Inequalities and Saddle Point Problems with Relative Inexact Information
 Conference Abstracts

The deadline for abstracts submission is moved to February, 29, 2024.

Submission of abstracts and papers for conference proceedings is made via EquinOCS system: https://equinocs.springernature.com/service/MOTOR2024

 Previous events

This conference continues the long-term traditions of the Baikal, Yekaterinburg, Novosibirsk and Omsk international and all-Russian conferences, which have a rich history and are regularly held in the Urals, Siberia and the Far East, starting from the seventies of the 20th.

Conference name Short name Since # in series Last event
Baikal International Triennial School Seminar on Methods of Optimization and Their Applications BITSS MOPT 1967 17 http://isem.irk.ru
Mathematical Programming and Applications MPF (MPA) 1972 15 http://mpa.imm.uran.ru
Discrete Optimization and Operations Research DOOR 1996 9 http://www.math.nsc.ru
Optimization Problems and their Applications OPTA 1997 7 http://opta18.oscsbras.ru
 About MOTOR

Since 2019, four well-known conferences have merged into one common cycle under the new name MOTOR, expanding geography and involving an increasing number of specialists in the field of optimization, operations research and their applications.

Conference name Dates Venue Proceedings
MOTOR 2023 Jul. 2-8, 2023 Ekaterinburg, Russia Vol.1 Vol.2
MOTOR 2022 Jul. 2-6, 2022 Petrozavodsk, Russia Vol.1 Vol.2
MOTOR 2021 Jul. 5-10, 2021 Irkutsk-Baikal, Russia Vol.1 Vol.2
MOTOR 2020 Jul. 6-10, 2020 Novosibirsk (online), Russia Vol.1 Vol.2
MOTOR 2019 Jul. 8-12, 2019 Ekaterinburg, Russia Vol.1 Vol.2
 Location

The conference will be held in the picturesque green area of Omsk at the Cronwel Park Nika. The Cronwell Park Nika Hotel meets high standards of hotel service quality, which allows it to be among the best hotels in Omsk. There are equipped conference rooms for events and excellent conditions for guests to relax.

Cronwell Park Nika

644015, Russia, Omsk, st. Suvorova, 110

https://nika.cronwell.com/about/index.php

 Contacts
13, Pevtsova str., 644099, Omsk, Russia - 99,
Omsk Division of Sobolev Institute of Mathematics SB RAS.
tel.: (3812) 236739,
E-mail: motor24@ofim.oscsbras.ru
 Registration fees
Early bird (up to May 15) After May 16 or on site
Student (undergraduate / graduate / PhD) 3000 rub 4000 rub
Regular 5000 rub 7000 rub
Online 1000 rub 2000 rub
 Organizers and sponsors
The Conference is supported by the Mathematical Center in Akademgorodok under the agreement No. 075-15-2022-282 with the Ministry of Science and Higher Education of the Russian Federation.
©2024, Omsk Department of Sobolev Institute of Mathematics, Siberian Branch of the Russian Academy of Sciences.