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8th International Conference on Optimization and Applications, OPTIMA 2017

作者： Strekalovsky, Alexander S. Matrosov Institute for System Dynamics and Control Theory SB RAS Lermontov st. 134 Irkutsk664033 Russia

This paper addresses the nonconvex optimization problem with the cost function and constraints given by d.c. functions. The original problem is reduced to a problem without inequality and equality constraints by means of the exact penalization techniques. Furthermore, the penalized problem is presented as a d.c. minimization problem. For the latter problem we develop the global optimality conditions (GOCs) which reduce the nonconvex optimization problem to a family of convex problems. In the paper the properties of the GOCs are investigated. The effectiveness of the GOCs is demonstrated by examples. © Copyright by the paper's authors.

关键词： Cost functions

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On numerical solution of specially constructed quadratic bilevel test problems 8

On numerical solution of specially constructed quadratic bil...

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8th International Conference on Optimization and Applications, OPTIMA 2017

作者： Orlov, Andrei V. Matrosov Institute for System Dynamics and Control Theory of Siberian Branch of RAS Lermontov St. 134 Irkutsk664033 Russia

This paper addresses the bilevel programming problems (BPPs) with the quadratic objective functions at the upper and the lower levels. The new solution method for such BPPs is developed. The main feature of the approach proposed is employment of the original A.S. Strekalovsky's Global Search theory. Numerical testing of the method on specially constructed instances demonstrated the efficiency of the approach. © Copyright by the paper's authors.

关键词： Numerical methods

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German-Russian astroparticle data life cycle initiative

arXiv

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arXiv 2019年

作者： Haungs, Andreas Bychkov, Igor Dubenskaya, Julia Fedorov, Oleg Heiss, Andreas Kang, Donghwa Kazarina, Yulia Korosteleva, Elena Kostunin, Dmitriy Kryukov, Alexander Mikhailov, Andrey Nguyen, Minh-Duc Polgart, Frank Polyakov, Stanislav Postnikov, Evgeny Shigarov, Alexey Shipilov, Dmitry Streit, Achim Tokareva, Victoria Wochele, Doris Wochele, Jürgen Zhurov, Dmitry Karlsruhe Institute of Technology IKP Karlsruhe76021 Germany Matrosov Inst. f. System Dynamics and Control Theory Irkutsk664033 Russia Irkutsk State University Irkutsk664003 Russia Lomonosov Moscow State University SINP Moscow119991 Russia Irkutsk State University Applied Physics Institute Irkutsk664003 Russia Karlsruhe Institute of Technology SCC Karlsruhe76021 Germany DESY Zeuthen15738 Germany

A data life cycle (DLC) is a high-level data processing pipeline that involves data acquisition, event reconstruction, data analysis, publication, archiving, and sharing. For astroparticle physics a DLC is particularly important due to the geographical and content diversity of the research field. A dedicated and experiment spanning analysis and data centre would ensure that multi-messenger analyses can be carried out using state-of-the-art methods. The German-Russian Astroparticle Data Life Cycle Initiative (GRADLCI) is a joint project of the KASCADE-Grande and TAIGA collaborations, aimed at developing a concept and creating a DLC prototype that takes into account the data processing features specific for the research field. An open science system based on the KASCADE Cosmic Ray Data Centre (KCDC), which is a web-based platform to provide the astroparticle physics data for the general public, must also include effective methods for distributed data storage algorithms and techniques to allow the community to perform simulations and analyses with sophisticated machine learning methods. The aim is to achieve more efficient analyses of the data collected in different, globally dispersed observatories, as well as a modern education to Big Data Scientist in the synergy between basic research and the information society. The contribution covers the status and future plans of the initiative. Copyright © 2019, The Authors. All rights reserved.

关键词： Data acquisition

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Multi-Agent Approach for Dynamic Elasticity of Virtual Machines Provisioning in Heterogeneous Distributed Computing Environment

Multi-Agent Approach for Dynamic Elasticity of Virtual Machi...

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International Conference on High Performance Computing & Simulation (HPCS)

作者： Alexander Feoktistov Ivan Sidorov Andrei Tchernykh Alexei Edelev Valery Zorkalzev Roman Kostromin Sergey Gorsky Igor Bychkov Arutyun Avetisyan Matrosov Institute for System Dynamics and Control Theory of the Siberian Branch of the Russian Academy of Sciences Irkutsk Russia Matrosov Inst. for Syst. Dynamics & Control Theor. Irkutsk Russia Ivannikov Institute for System Programming of the Russian Academy of Sciences Moscow Russia Melentiev Energy Systems Institute of the Siberian Branch of the Russian Academy of Sciences Irkutsk Russia

ISBN: (纸本)9781538678800

We address dynamic elasticity issues of VM provisioning in a heterogeneous distributed computing environment that integrates resources of a data center. We consider the scenario when the center includes dedicated resources (private cloud) for providing virtualized service and non-dedicated resources for Grid-computing. Existing platforms for the resource virtualization does not support management of such an infrastructure. We propose an approach to a job management based on the dynamic elasticity of virtual machines provisioning using resources of both types. We develop the multi¬agent job scheduler for dedicated resources and hypervisor shell to launch virtual machines through queues of resource management systems in non-dedicated resources. The scheduler provides a dynamic elasticity of virtual machine provisioning. Advantages of the offered approach to the resource virtualization are demonstrated by an example of a job flow management for a scalable application to solve the complicated practical problem. It is related to the energy security of Vietnam. Provided experiments show that using the developed tools together with the platform for the resource virtualization enables agents to significantly speed up the problem-solving process.

关键词： Cloud computing Resource management Dynamic scheduling Virtual machine monitors Elasticity Virtual machining

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Nonconvex optimization: From global optimality conditions to numerical methods

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AIP Conference Proceedings 2019年第1期2070卷

作者： Alexander Strekalovskiy Matrosov Institute for System Dynamics and Control Theory of Siberian Branch of Russian Academy of Sciences Lermontov St. 134 Irkutsk 664033 Russia

The paper addresses the nonconvex nonsmooth optimization problem with the cost function and equality and inequality constraints given by d.c. functions. The original problem is reduced to a problem without constraints with the help of the exact penalization theory. After that, the penalized problem is represented as a d.c. minimization problem without constraints, for which the new mathematical tools under the form of global optimality conditions (GOCs) are developed. The GOCs reduce the nonconvex problem in question to a family of convex (linearized with respect to the basic nonconvexities) problems. On the base of the proposed theory we develop numerical methods of local and global search for the problem in question.

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An algorithm for packing circles of two types in a fixed size container with non-euclidean metric 6

An algorithm for packing circles of two types in a fixed siz...

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Supplementary 6th International Conference on Analysis of Images, Social Networks and Texts, AIST-SUP 2017

作者： Kazakov, Alexander L. Lempert, Anna A. Le, Quang Mung Matrosov Institute for System Dynamics and Control Theory SB RAS Irkutsk Russia Irkutsk National Research Technical University Irkutsk Russia

The paper deals with the problem of optimal packing of two sets of circles (2-D spheres) into a simply connected container. The number of circles is given. The radii of these circles are equal within each set, but, generally speaking, they differ between sets. There are two different statements of a such problem. The simplest one is when the circles of a larger radius are located first, and then smaller circles are packed into the gaps. Solving of a such problem, in fact, reduces to a two-fold solution of the equal circles packing problem. However, the procedure is complicated by the fact that in the second solution the container will be a multiply connected set. We consider a more complex formulation: it is required to maximize the radii of the circles when their ratio is fixed. The circle packing problem is usually studied in the case when the distance between points is Euclidean and even then belongs to the class of NP-hard problems. We assume that the distance is determined by means of some special metric, which, generally speaking, is not Euclidean. The special numerical algorithm is suggested and implemented. It based on optical-geometric approach, which is developed by the authors in recent years and previously used only for packing circles of equal radius. The results of computational experiment are presented and discussed.

关键词： Containers

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Iterative algorithms for optimal packing construction in inhomogeneous metrics 48

Iterative algorithms for optimal packing construction in inh...

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48th International Youth School Conference "Modern Problems in Mathematics and its Applications", SoProMat 2017

作者： Lebedev, Pavel D. Lempert, Anna A. Krasovskii Institute of Mathematics and Mechanics Yekaterinburg Russia Matrosov Institute for System Dynamics and Control Theory Siberian Branch of Russian Academy of Sciences Irkutsk Russia

The problem of packing of equal circles in the convex bounded 2-D sets is considered. The metric is significantly different from the Euclidean one. Here the distance between points is equal to the minimal time that requires for passing from one point to another. In other words, the shortest route between two points is a curve, to spend the least time. The optimality criterion for the packing is the radius of a fix number of circles. The proposed algorithm includes the computational method for constructing boundaries of packing circles as wave fronts, based on principles of geometric optics. To maximize the radius, we use the iterative procedures that simulate the repulsion of circle centers from the boundaries of adjacent packing elements and from the boundary of a convex set. They based on the Chebyshev center constructions, which make it possible to form a displacement vector in the required direction. Numerical modeling for the sets of different geometries and for the different distribution of wave propagation velocities is carried out. The results are visualized. Copyright © by the paper's authors. Copying permitted for private and academic purposes.

关键词： Set theory

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A Shared Memory Parallel Heuristic Algorithm for the Large-Scale p-Median Problem 1

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International Conference on Optimization and Decision Science, ODS 2017

作者： Vasilyev, Igor Ushakov, Anton Matrosov Institute for System Dynamics and Control Theory of the Siberian Branch of the Russian Academy of Sciences 134 Lermontov str. Irkutsk664033 Russia

ISBN: (数字)9783319673080

ISBN: (纸本)9783319673073

We develop a modified hybrid sequential Lagrangean heuristic for the p-median problem and its shared memory parallel implementation using the OpenMP interface. The algorithm is based on finding the sequences of lower and upper bounds for the optimal value by use of a Lagrangean relaxation method with a subgradient column generation and a core selection approach in combination with a simulated annealing. The parallel algorithm is implemented using the shared memory (OpenMP) technology. The algorithm is then tested and compared with the most effective modern methods on a set of test instances taken from the literature. © 2017, Springer International Publishing AG.

关键词： Simulated annealing

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Preface

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CEUR Workshop Proceedings 2019年 2430卷

作者： Bychkov, Igor Tchernykh, Andrei Dutykh, Denys Matrosov Institute for System Dynamics and Control Theory of the Siberian Branch of the Russian Academy of Sciences Irkutsk Russia CICESE Research Center Ensenada Mexico University of Savoie France

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Air pollution and population morbidity forecasting with artificial neural networks

Air pollution and population morbidity forecasting with arti...

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International Conference and Early Career Scientists School on Environmental Observations, Modeling and Information systems, ENVIROMIS 2018

作者： Gornov, A Yu Zarodnyuk, T.S. Efimova, N.V. Institute for System Dynamics and Control Theory Siberian Branch of Russian Academy of Sciences Lermontov str. 134 Post Box 64033 Irkutsk Russia East-Siberian Institute of Medical and Ecological Research 12a District 3 Angarsk665827 Russia

Incidence prediction models for urban population have not yielded consistent or highly accurate results. The complex nature of the interrelationship between "environmental factors and incidence" has many nonlinear associations with outcomes. We explore artificial neural networks (ANNs) to predict the complex interactions between the risk factors of incidence among the urban population. ANN modeling using a standard feed-forward, back-propagation neural network with three layers (i.e., an input layer, a hidden layer, and an output layer) is used to predict the incidences of diseases of children and adults. A receiver-operating characteristic (ROC) analysis is used to assess the model accuracy. We develop a mathematical model taking into account factors of natural, anthropogenic, and social environments. The model effectiveness is proved by computing experiments for the Bratsk industrial centre (Irkutsk region, Russia). Optimal air pollution levels are offered to achieve a background morbidity level among different age groups of the population. The prediction of incidence is most accurate when using the ANN model with several univariate influences on the outcome. An incorporation of some computerized learning systems might improve decision making and outcome prediction. © Published under licence by IOP Publishing Ltd.

关键词： Forecasting

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