МЕЖДУНАРОДНАЯ КОНФЕРЕНЦИЯ

ТЕОРИЯ МАТЕМАТИЧЕСКОЙ ОПТИМИЗАЦИИ И ИССЛЕДОВАНИЕ ОПЕРАЦИЙ

(MOTOR 2019)

8–12 июля, 2019, Екатеринбург
© alshevskix.livejournal.com

Новости

July 11, 2019

June 27, 2019

June 24, 2019
Добавлена информация об обзорной экскурсии.

June 23, 2019

June 14, 2019

June 12, 2019
Вышел сборник LNCS.

О конференции

Международная конференция "Теория математической оптимизации и исследование операций" (MOTOR2019) http://motor2019.uran.ru будет проводиться 8-12 июля 2019г. в живописном месте в окрестностях г.Екатеринбурга (Россия), столицы Урала, на границе Европы и Азии.

Цель планируемого научного мероприятия состоит в объединении широкого круга исследователей и специалистов в области актуальных проблем математического программирования, глобальной и дискретной оптимизации, теории вычислительной сложности и комбинаторных алгоритмов, оптимального управления и теории игр, а также практических приложений в исследовании операций, математической экономике и анализе данных.

Важные даты

Отправка аннотаций:
15 января, 2019
1 февраля, 2019
Отправка полных статей:
1 февраля, 2019
15 февраля, 2019
Принятие доклада:
15 марта, 2019
27 марта, 2019
Отправка статей в печать:
  LNCS:
7 апреля, 2019
  CCIS:
30 июня, 2019
Даты конференции:
8-12 июля, 2019

Контакты:

История

Настоящая конференция объединяет четыре известные международные и всероссийские конференции в области оптимизации, исследования операций и приложений, регулярно проводимые на территории Урала, Сибири и Дальнего Востока с середины XX в.

Конференция
Год основания
Число
мероприятий
Сайт

Байкальская международная школа семинар "Методы оптимизации и их приложения" (MOPT)

1969

17

Всероссийская конференция "Математическое программирование и приложения" (MPA)

1972

15

Международная конференция "Дискретная оптимизация и исследование операций" (DOOR)

1996

9

Международная конференция "Проблемы оптимизации и их приложения" (OPTA)

1997

7

Тематика конференции

  • математическое программирование
  • глобальная оптимизация
  • целочисленное программирование и комбинаторная оптимизация
  • вычислительная сложность, приближенные алгоритмы, схемы, оценки, эвристики и метаэвристики
  • оптимальное управление и теория игр
  • оптимизация и теория приближений функций
  • оптимизация в статистическом обучении и анализе данных
  • приложения в исследовании операций: задачи составления расписаний, маршрутизации, размещения предприятий, упаковки и раскроя, управления производством и т.д.

Организаторы конференции

Председатели программного комитета

Профессор Ю.А. Кочетов
Институт математики СО РАН (Россия)
Профессор П.М. Пардалос
Университет Флориды (США)
Профессор РАН М.Ю. Хачай
Институт математики и механики (ИММ) УрО РАН (Россия)

Программный комитет

(to be extended)

Prof. E. Amirgaliev
Suleyman Demirel University, Kazakhstan
Проф. А.С. Антипин
Вычислительный центр им. А.А. Дородницына РАН, Россия
Проф. А.П. Афанасьев
Институт проблем передачи информации им. А.А. Харкевича РАН, Россия
Prof. A. Bagirov
Federation University Australia, Australia
Prof. E. Bampis
Sorbonne Université, France
Prof. O. Battaia
ISAE-Supaero, Toulouse, France
Dr. R. van Bevern
Novosibirsk State University, Russia
Акад. В.И. Бердышев
Институт математики и механики им. Н.Н.Красовского УрО РАН, Россия
Проф. В.Л. Береснев
Институт математики имени С.Л. Соболева РАН, Россия
Prof. O. Burdakov
Linköping University, Sweden
Prof. S. Butenko
Texas A&M University, USA
Проф. И.А. Быкадоров
Институт математики имени С.Л. Соболева РАН, Россия
Чл. корр. В.В. Васин
Институт математики и механики им. Н.Н.Красовского УрО РАН, Россия
Проф. Э.Х. Гимади
Институт математики имени С.Л. Соболева РАН, Россия
Проф. А.Ю. Горнов
Институт динамики систем и теории управления имени В.М. Матросова РАН, Россия
Проф. М.И. Гусев
Институт математики и механики им. Н.Н.Красовского УрО РАН, Россия
Prof. A. Grigoriev
Maastricht University, Netherlands
Prof. T. Davidovic
Mathematical Institute SANU, Serbia
Prof. V. Deineko
Warwick University, GB
Prof. S. Dempe
Freiberg University, Germany
Prof. A. Dolgui
IMT Atlantique, France
Акад. Ю.Г. Евтушенко
Вычислительный центр им. А.А. Дородницына РАН, Россия
Проф. А.В. Еремеев
Омский государственный университет им. Ф.М. Достоевского, Россия
Проф. А.И. Ерзин
Институт математики имени С.Л. Соболева РАН, Россия
Prof. V. Kalashnikov
ITESM, Campus Monterrey, Mexico
Проф. В.А. Калягин
Высшая школа экономики, Россия
Проф. А.Л. Казаков
Институт динамики систем и теории управления имени В.М. Матросова РАН, Россия
Проф. А.В. Кельманов
Институт математики имени С.Л. Соболева РАН, Россия
Проф. А.И. Кибзун
Московский авиационный институт, Россия
Prof. D. (David) Kim
Kennesaw State University, USA
Prof. M.Y. Kovalyov
United Institute of Informatics Problems NASB, Belarus
Проф. И.В. Коннов
Казанский федеральный университет, Россия
Проф. А.В. Кононов
Институт математики имени С.Л. Соболева РАН, Россия
Prof. V. Kotov
Belarusian State University, Belarus
Prof. I. Kotsireas
University of Waterloo, Canada
Проф. А.А. Лазарев
Институт проблем управления им. В.А. Трапезникова РАН, Россия
Prof. V. Levit
Ariel University, Israel
Prof. B. M.T. Lin
National Chiao Tung University, Hsinchu, Taiwan
Чл. корр. Н.Ю. Лукоянов
Институт математики и механики им. Н.Н.Красовского УрО РАН, Россия
Проф. В.В. Мазалов
Институт прикладных математических исследований Карельского научного центра РАН, Россия
Prof. N. Mladenovic
Emirates College of Technologies, Abu Dhabi, UAE
Prof. Y. Nikulin
University of Turku, Finland
Проф. Е.А. Нурминский
Дальневосточный федеральный университет, Россия
Проф. Л.А.Петросян
Санкт-Петербургский университет, Россия
Проф. А.А. Петунин
Уральский федеральный университет, Россия
Проф. Б.Т. Поляк
Институт проблем управления им. В.А. Трапезникова РАН, Россия
Проф. Л.Д. Попов
Институт математики и механики им. Н.Н.Красовского УрО РАН, Россия
Проф. М.А. Посыпкин
Вычислительный центр им. А.А. Дородницына РАН, Россия
Prof. O. Prokopyev
University of Pittsburgh, USA
Проф. А.В. Пяткин
Институт математики имени С.Л. Соболева РАН, Россия
Prof. S. Raha
Indian Institute of Science, India
Акад. К.В. Рудаков
Вычислительный центр им. А.А. Дородницына РАН, Россия
Prof. K. Sabo
University of Osijek, Croatia
Prof. L. Sakalauskas
Univeristy of Vilnius, Lithuania
Проф. Е.С. Семенкин
Сибирский государственный университет науки и технологий им. М.Ф. Решетнева
Prof. Y. Sergeev
University of Calabria, Italy
Prof. N. Shakhlevich
University of Leeds, GB
Prof. A. Sifaleras
University of Macedonia, Greece
Проф. В.Д. Скарин
Институт математики и механики им. Н.Н.Красовского УрО РАН, Россия
Проф. А.С. Стрекаловский
Институт динамики систем и теории управления имени В.М. Матросова РАН, Россия
Prof. V. Strusevich
University of Greenwich, GB
Prof. F. Fomin
University of Bergen, Norway
Проф. О.В. Хамисов
Институт систем энергетики им. Л.А. Мелентьева РАН, Россия
Prof. T. Tchemisova
University of Aveiro, Portugal
Проф. В.И.Ухоботов
Челябинский государственный университет, Россия
Чл. корр. В.Н. Ушаков
Институт математики и механики им. Н.Н.Красовского УрО РАН, Россия
Prof. M. Jacimovic
University of Montenegro, Montenegro
Проф. А.А. Шананин
Московский физико-технический институт, Россия

Индустриальная секция

Проф. Д.Н. Гайнанов
Уральский федеральный университет, Россия
А.А. Курочкин
Институт математики имени С.Л. Соболева РАН, Россия

Организационный комитет

Проф. М.Ю. Хачай (пред.)
ИММ УрО РАН
К.С. Кобылкин (пред.)
ИММ УрО РАН
А.Н. Борбунов
ИММ УрО РАН
П.А. Кононова
Институт математики им. С.Л. Соболева РАН, Россия
Ф.А. Корнилов
ИММ УрО РАН
Г.Ф. Корнилова
ИММ УрО РАН
М.А. Костина
ИММ УрО РАН
В.Б. Костоусов
ИММ УрО РАН
Н.А. Кочетова
Институт математики им. С.Л. Соболева РАН, Россия
Т.В.Медведев
Высшая школа экономики, Россия
Е.Д. Незнахина
ИММ УрО РАН
Ю.Ю. Огородников
ИММ УрО РАН
М.К. Пасынков
ИММ УрО РАН
М.И. Поберий
ИММ УрО РАН
А.И. Смирнов
ИММ УрО РАН

Приглашенные докладчики

Plenary lectures

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Prof. Olga Battaia

ISAE-Supaero, Toulouse
France

Decision under ignorance: a comparison of existing criteria in a context of linear programming

Abstract: Decision or optimization problems often arise in an uncertain context. Depending on available information, several approaches have been proposed to model this uncertainty. In this talk, we focus on the case of low knowledge on possible states, namely decision under ignorance. In this case the decision-maker is able to give the set of possible values of optimization problem parameters but she/he is not able to differentiate them. We compare a set of criteria that can be used in this case on the example of a linear programming problem and discuss some possible applications.


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Prof. Oleg Burdakov

Linkoping University
Sweden

Node partitioning and cycles creation problem

Abstract: We present a new class of network optimization problems, which extend the classical NP-hard travelling salesman problem. It is formulated as follows. Given a graph with a certain time associated with each node and each arc, a feasible partition of the nodes in subsets is such that, for each subset, there exists a Hamiltonian cycle whose travelling time is below the time associated with each node in the tour. It is required to find a feasible partitioning which minimizes the number of such cycles. Problems of this kind are typical in numerous applications, where services are repeatedly provided for a set of customers. For each customer, there is a critical time within which a service must be repeated. Given the travelling time between the customers, the set of customers is partitioned so that each subset is served by one agent in a cyclic manner without violating any individual critical time requirement. The number of agents is minimized. As an example, we consider a problem, in which a fleet of unmanned aerial vehicles is used for area patrolling. We introduce an mixed integer programming formulation of the node partitioning and cycles creation problem, and also heuristic algorithms for solving this problem. Results of numerical experiments are presented.

Joint work with: Kai Hoppmann, Thorsten Koch and Gioni Mexi (ZIB, Berlin, Germany)


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Prof. Christoph Dürr

Sorbonne Université
France

Bijective analysis of online algorithms

Abstract: In the online computing framework the instance arrives in form a request sequence, every request must be served immediately, through a decision, which generates some cost. Think at the paging problem for memory caches. The goal in this research area is to identify the best strategy, also called online algorithm. Classically this is done through the competitive analysis, i.e. the performance of an online algorithm is compared with the optimal offline solution. The goal is to find an algorithm which minimizes this ratio over the worst case instance. You would say that algorithm A is better than algorithm B if it has a smaller ratio. However there are situations where two algorithms have the same ratio, still in practice one is better than the other. So people came up with a different technique to compare online algorithms directly with each other, rather than through the optimal offline solution. The bijective analysis is one of them. I would do a survey on this technique, and talk about a related personal work: Best-of-two-worlds analysis of online search, with Spyros Angelopoulos and Shendan Jin.


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Prof. Alexander Grigoriev

Maastricht University
Netherlands

A survey on possible and impossible attempts to solve the treewidth problem via ILPs

Abstract: We survey a number of integer programming formulations for the pathwidth and for the treewidth problems. The attempts to find good formulations for the problems span the period of 15 years, yet without any true success. Nevertheless, some formulations provide potentially useful frameworks for attacking these notorious problems. Some others are just curious and interesting fruits of mathematical imagination.


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Prof. Mikhail Kovalyov

United Institute of Informatics Problems NASB
Belarus

No-idle scheduling of unit-time jobs with release dates and deadlines on parallel machines

Abstract: While the problem of scheduling unit-time jobs with release dates and deadlines on parallel machines is polynomially solvable via a reduction to the assignment problem, the no-idle requirement destroys this reduction and makes the problem challenging. In the presentation, a number of properties of this problem are reported, and heuristic and optimal algorithms based on these properties are described.


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Prof. Vadim Levit

Ariel University
Israel

Critical and Maximum Independent Sets Revisited

Abstract: A set of vertices of a graph is independent if no two its vertices are adjacent. A set is critical if the difference between its size and the size of its neighborhood is maximum. Critical independent sets define an important area of research due to their close relationships with the well-known NP-hard problem of finding a maximum independent set. Actually, every critical independent set is contained in a maximum independent set, while a maximum critical independent set can be found in polynomial time. If S is an independent set such that there is a matching from its neighborhood into S, then it is a crown. It is known that every critical independent set forms a crown. A graph is König-Egerváry if every maximum independent set is a crown. Crowns are also accepted as important tools for fixed parameter tractable problems. For instance, the size of the vertex cover can be substantially reduced by deleting both the vertices of a crown and its neighborhood. In this presentation, we discuss various connections between unions and intersections of maximum (critical) independent sets of graphs, which lead to deeper understanding of crown structures, in general, and König-Egerváry graphs, in particular.


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Prof. Bertrand M.T. Lin

National Chiao Tung University, Hsinchu
Taiwan

An Overview of the Relocation Problem

Abstract: The relocation problem is formulated from a municipal redevelopment project in east Boston. In its abstract form, the relocation problem incorporates a generalized resource constraint in which the amount of the resource returned by a completed activity is not necessarily the same as that the activity has acquired for commencing the processing. We will first introduce the connection of the relocation problem to flow shop scheduling. Several traditional scheduling models with the generalized resource constraints have been proposed investigated. We will review existing results, suggest new models and present several open questions.


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Prof. Natalia Shakhlevich

University of Leeds
United Kingdom

On a New Approach for Optimization under Uncertainty

Abstract: Research on decision making under uncertainty has a long history of study. Still theoretical findings have strong limitations: stochastic programming requires probability distributions for uncertain parameters which are often hard to specify; robust optimisation essentially relies on worst-case scenarios which can be over-pessimistic and far from realistic scenarios; stability analysis explores optimal solutions which can be hard to find even for well predicted scenarios. As an alternative approach, we propose a new system model based on the concept of resiliency. Resilient solutions are not required to be optimal, but they should keep quality guarantees for the widest range of uncertain problem parameters. The talk illustrates key steps of resiliency analysis considering examples of 0/1 combinatorial optimisation problems.


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Prof. Angelo Sifaleras

University of Macedonia
Greece

Exterior Point Simplex-type Algorithms for Linear and Network Optimization Problems

Abstract: Two decades of research led to the development of a number of efficient algorithms that can be classified as exterior point simplex-type. This type of algorithms can cross over the infeasible region of the primal (dual) problem and find an optimal solution reducing the number of iterations needed. Thus, such approaches aim to find an efficient way to get to an optimal basis via a series of infeasible ones. In this lecture, we present the developments in exterior point simplex-type algorithms for linear and network optimization problems, over the recent years. We also present other approaches that, in a similar way, do not preserve primal or dual feasibility at each iteration such as the monotonic build-up Simplex algorithms and the criss-cross methods, and also discuss some open research problems.


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Prof. Vitaly Strusevich

University of Greenwich
United Kingdom

Design of Fully Polynomial Time Approximation Schemes for Non-linear Boolean Programming Problems

Abstract: The talk is aimed at describing various techniques used for designing fully-polynomial approximation schemes (FPTAS) for problems of minimizing and maximizing non-linear non-separable functions of Boolean variables, either with no additional constraints or with linear knapsack constraints. Most of the reported results are on optimizing a special quadratic function known as the half-product, which has numerous scheduling applications. Besides, problems with a more general objective and nested linear constraints are considered and a design of an FPTAS based on the K-approximation calculus is discussed.


Tutorials

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Prof. Tatjana Davidović

Mathematical Institute of the Serbian Academy of Sciences and Arts
Serbia

Distributed memory based parallelization of metaheuristic methods

Abstract: Metaheuristics represent powerful tools for addressing hard combinatorial optimization problems. However, real life instances usually cannot be treated efficiently by the means of computing times. Moreover, a major issue in metaheuristic design and calibration is to provide high performance solutions for a variety of problems. Parallel metaheuristics aim to address both issues. The main goal of parallelization is to speed up the computations by dividing the total amount of work between several processors. Parallelization of stochastic algorithms, such as metaheuristics may involve several additional goals. Besides speeding up the search (i.e., reducing the search time), it could be possible to: improve the quality of the obtained solutions (by enabling searching through different parts of the solution space); improve the robustness of the search (in terms of solving different optimization problems and different instances of a given problem in an effective manner; robustness may also be measured in terms of the sensitivity of the metaheuristic to its parameters); and solve large-scale problems (i.e., solve very large instances that cannot be even stored in the memory of a sequential machine). A combination of gains may also be obtained: parallel execution can enable an efficient search through different regions of the solution space, yielding an improvement of the quality of the final solution within a smaller amount of execution time. The objective of this talk is to present a state-of-the-art survey of the main ideas and strategies related to the parallelization of metaheuristic methods. Various paradigms related to the development of parallel metaheuristics are explained. Among them, communications, synchronization, and control aspects are identified as the most relevant. Implementation issues are also discussed, pointing out the characteristics of shared and distributed memory multiprocessors as target architectures. All these topics are illustrated by the examples from recent literature related to the parallelization of various meta-heuristic methods, with the focus on distributed memory parallelization of Variable Neighborhood Search (VNS) and Bee Colony Optimization (BCO) using Message Passing Interface (MPI) communication protocol.


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Prof. Stephan Dempe

TU Bergakademie Freiberg
Germany

Bilevel optimization: The Model and its Transformations

Abstract: Bilevel (or hierarchical) optimization problems aim to minimize one function subject to (a subset of) the graph of the solution set mapping of a second, parameter dependent optimization problem. The parameter is the decision variable of the socalled leader, the optimization problem describing the constraints is the problem of the follower. These problems have a large number of applications in science, engineering, economics. To investigate and solve them, they need to be transformed into a single-level optimization problem. For that different approaches can be used.
  1) If the follower’s problem is regular and convex, it can be replaced using the Karush-Kuhn-Tucker conditions. The result is a so-called Mathematical Program with Equilibrium Constraints. In these nonconvex optimization problems, the Mangasarian-Fromovitz constraint qualification is violated at every feasible point. Solution algorithms converge (under suitable assumptions) to stationary points which are, in general, not related to stationary points of the bilevel optimization problem. To overcome this unpleasant situation, a certain regularization approach can be used. Another approach uses the transformation to a mixed integer (nonlinear) optimization problem.
  2) If the optimal value function of the follower’s problem is used, a nonconvex, nonsmooth optimization problem arises. Again, the (now nonsmooth) Mangasarian-Fromovitz constraint qualification is violated at every feasible point. If the optimal value function is convex or concave, its approximation is helpful to describe a solution algorithm. Optimality conditions can be derived using partial calmness or a certain penalization approach.
  3) The problem can be reformulated as a generalized Nash equilibrium problem.
Topic of the lecture is the introduction of the model together with some surprising properties and a short overview over promising accesses to investigate and solve it.


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Prof. Oleg Khamisov

Melentiev Energy Systems Institute SB RAS
Russia

The fundamental role of concave programming in continuous global optimization

Abstract: A comprehansive description of connections between concave programming and other branches of global optimization like Lipschitz optimization, d.c. optimization etc. is given. It is shown that in general solution of almost every global optimization problem can reduced to solution of a sequence of concave programming problems. Modern concave optimization technology including cuts, branch and bounds, branch and cuts and so on as well as the corresponding extensions to different global optimization problems are presented. A part of the talk is devoted to the connection between concave and mixed 0-1 linear programming.


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Prof. Alexander Kononov

Sobolev Institute of Mathematics
Russia

Primal-dual Method and Online Problems

Abstract: The primal-dual method is a powerful tool in the design of approximate algorithms for combinatorial optimization problems. In our tutorial we discuss how this method can be extended to develop online algorithms. The tutorial is based on the survey by N. Buchbinder and J. Naor and the web-presentation by N. Bansal.


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Prof. Nenad Mladenovic

Emirates College of Technologies
Abu Dhabi, UAE

Solving nonlinear system of equations as an optimization problem

Abstract: The Nonlinear System of Equations (NSE) problem is usually transformed into an equivalent optimization problem, with an objective function that allows us to find all the zeros. Instead of the usual sum-of-squares objective function, the new objective function is presented as the sum of absolute values. Theoretical investigation confirms that the new objective function provides more accurate solutions regardless of the optimization method used. In addition, we achieve increased precision at the expense of reduced smoothness. In this paper, we propose the continuous variable neighbor-hood search method for finding all the solutions to a NSEs. Computational analysis of standard test instances shows that the proposed method is more precise and much faster than two recently developed methods. Similar conclusions are drawn by comparing the proposed method with many other methods in the literature.

Joint work with: Jun Pei, Zorica Drazic, Milan Drazic, Panos M. Pardalos


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Prof. Evgeni A. Nurminski

Far Eastern Federal University
Russia

Projection Problems and Problems with Projection

Abstract: This lecture reviews the state of the art for probably the most common computational operation in applied mathematics --- projection, which can be also considered as the problem of finding the least norm element (LNE) in a given subset of a linear vector space. The special attention in the lecture will be given to Euclidean or orthogonal projection, but we plan to discuss another norms as well. Projection is computationally intensive operation even for relatively simple sets like canonical simplexes and special algorithms are a way more efficient than off-the-shelf quadratic programming methods especially for large-scale problems. Large-scale projection problems can be decomposed in different sequential or parallel manner as extension of celebrated Kaczmarz sequential projection procedure and block-row action methods. We discuss also the problem of numerical instability of projection operation which is quite common in such applications as new optimization algorithms, linear programming, machine learning and automatic classification.


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Prof. Alexander Strekalovsky

Matrosov Institute for System Dynamics and Control Theory SB RAS
Russia

Modern methods of nonconvex optimization

Abstract: We address the nonconvex optimization problem with the cost function and equality and inequality constraints given by d.c. functions. The linear space of d.c. functions possesses a number of very attractive properties. For example, every continuous function can be approximated at any desirable accuracy by a d.c. function and any twice differentiable function belongs to the DC space. In addition, any lower semicontinuous (l.s.c.) function can be approximated at any precision by a sequence of continuous functions. Furthermore, provided that for the optimization problem under study we proposed the new Global Optimality Conditions (GOCs), which have been published in the English and Russian languages. The natural question arises: is it possible to construct a computational scheme based on the GOCs (otherwise, what are they for?) that would allow us not only to generate critical points (like the KKT-vectors) but to escape any local pitfall, which makes it possible to reach a global solution to the problem in question? First of all, we recall that with the help of the Theory of Exact Penalization, the original d.c. problem was reduced to a problem without constraints. Moreover, it can be readily seen that this penalized problem is a d.c. problem as well. Furthermore, special Local Search Methods (LSMs) were developed and substantiated in view of their convergence features. In addition, the GOCs were generalized for the minimizing sequences in the penalized problem. A special theoretical method was proposed and its convergence properties were studied. We developed a Global Search Scheme (GSS) based on all theoretical results presented above, and, moreover, we were lucky to prove that the sequence produced by the GSS turned out to be minimizing in the original d.c. optimization problem. Finally, we developed a Global Search Method (GSM), combining the special LSM and the GSS proposed. The convergence of the GSM is also investigated under some natural assumptions. The first results of numerical testing of the approach will be demonstrated.

Публикации

Приглашаем авторов представить статьи, содержащие новые неопубликованные результаты по тематике конференции. Статьи объемом 12-15 страниц должны быть подготовлены в формате Springer LNCS и представлены в виде PDF, см. официальные правила Springer для авторов статей и Latex шаблоны LNCS. Прием работ проводится через систему Easychair, которая уже доступна.

Тезисы

Сборник тезисов

Труды конференции

Труды конференции будут опубликованы издательством Springer Nature в двух томах, в сериях Lecture Notes in Computer Science (LNCS) и Communications in Computer and Information Science (CCIS).




Lecture Notes in Computer Science

LNCS vol. 11548

Accepted papers

4
Ilya Chernykh and Ekaterina Lgotina
How the difference in travel time affects the optima localization for the routing open shop
6
Igor' Izmest'Ev and Viktor Ukhobotov
On a single-type differential game with a non-convex terminal set
12
René Van Bevern, Till Fluschnik and Oxana Tsidulko
On (1+ε)-approximate data reduction for the Rural Postman Problem
14
Artem Pyatkin and Mikhail Golovachev
Routing Open Shop with two nodes, unit processing times and equal number of jobs and machines
16
Maximilian John and Andreas Karrenbauer
Dynamic Sparsification for Quadratic Assignment Problems
26
Andrei Orlov and Tatiana Gruzdeva
The Local and Global Searches in Bilevel Problems with a Matrix Game at the Lower Level
28
Michael Khachay and Yuri Ogorodnikov
Approximation scheme for the Capacitated Vehicle Routing Problem with Time Windows and non-uniform demand
29
Sergey Lavlinskii, Artem Panin and Alexander Plyasunov
Stackelberg Model and Public–Private Partnerships in the Natural Resources Sector of Russia
34
Konstantin Kobylkin and Irina Dryakhlova
Approximation algorithms for piercing special families of hippodromes: an extended abstract
46
Sergey Khapugin and Andrey Melnikov
Local Search Approach for the Medianoid Problem with Multi-purpose Shopping Trips
50
Andrei Nikolaev
On vertex adjacencies in the polytope of pyramidal tours with step-backs
51
Igor Konnov and Olga Pinyagina
Splitting method with adaptive step-size
52
Anna Kozlova and Andrei Nikolaev
Simulated annealing approach to verify vertex adjacencies in the traveling salesperson polytope
55
Stephan Dempe
Computing local optimal solutions of the bilevel optimization problem using the KKT approach
68
Anna N. Rettieva
Coalition Stability in Dynamic Multicriteria Games
75
Victor Il'Ev, Svetlana Il'Eva and Alexander Morshinin
A 2-approximation algorithm for the graph 2-clustering problem
88
Valeriy Marakulin
Spatial equilibrium in a multidimensional space: an immigration-consistent division into countries centered at barycenter
92
Christof Defryn, Julian Golak, Alexander Grigoriev and Veerle Timmermans
Inland waterway efficiency through skipper collaboration and joint speed optimization
108
Sergey Ivanov and Irina Zhenevskaya
Estimation of the necessary sample size for approximation of stochastic optimization problems with probabilistic criteri
113
Dimitrije D. Čvokić, Yury Kochetov, Alexander Plyasunov and Aleksandar Savić
The competitive hub location under the price war
117
Mikhail Gusev
Estimates of the minimal eigenvalue of the controllability Gramian for a system containing a small parameter
123
Vitalii Arestov
Best approximation of a differentiation operator on the set of smooth functions with exactly or approximately given Fourier transform
124
Oxana Matviychuk
On ellipsoidal estimates for reachable sets of the control system
125
Ekaterina Kolpakova
Open-loop Strategies in Nonzero-sum Differential Game with Multilevel Hierarchy
132
Vitaly Zhadan
Variant of Simplex Method for Second-order Cone Programming
135
Anton Eremeev, Alexander Kelmanov, Mikhail Y. Kovalyov and Artem Pyatkin
Maximum Diversity Problem with Squared Euclidean Distance
139
Maria Barkova
On generating nonconvex optimization test problems
151
Leon Petrosyan and Yaroslavna B. Pankratova
Equilibrium and Cooperation in the Repeated Hierarchical Games
155
Dragan Urosevic, Yiad Ibrahim Yousef Alghoul, Zhazira Amirgaliyeva and Nenad Mladenovic
Less is more: Tabu search for Quadratic Bipartite Programming Problem
156
Boris Ananyev
Control Problem of Parabolic System with Incomplete Information
157
Marina Plekhanova
Problems of hard control for a class of degenerate fractional order evolution equations
158
Ildus Kuchkarov and Ovanes Petrosian
On a Class of Linear Quadratic Non-cooperative Differential Games with Continuous Updating
160
Anton Eremeev, Nikolay Tyunin and Alexander Yurkov
Non-Convex Quadratic Programming Problems in Short Wave Antenna Array Optimization
163
Vladislav Sovrasov
Comparison of several stochastic and deterministic derivative-free global optimization algorithms
165
Fedor Stonyakin, Darina Dvinskikh, Pavel Dvurechensky, Alexey Kroshnin, Olesya Kuznetsova, Artem Agafonov, Alexander Gasnikov, Alexander Turin, Cesar Uribe, Dmitry Pasechnyuk and Sergei Artamonov
Gradient Method for Problems with Inexact Model of the Objective
174
Vladimir Mazalov and Elena Parilina
Game of competition for opinion with two centers of influence
175
Sergey Semenov and Nikolai Zolotykh
A dynamic algorithm for constructing the dual representation of a polyhedral cone
176
Alexander Kononov, Julia Memar and Yakov Zinder
Scheduling with limited storage - a polynomial-time algorithm and efficient heuristics
177
Nadezhda Maltugueva, Nikolay Pogodaev and Olga Samsonyuk
Optimality conditions and numerical algorithms for hybrid systems
179
Dmitry Gribanov and Dmitry Malishev
Integer Conic Function Minimization Based on the Comparison Oracle
181
Yulia Kovalenko and Aleksey Zakharov
Pareto-based Hybrid Algorithms for the Bicriteria Asymmetric Travelling Salesman Problem
188
Anna Panasenko
A PTAS for One Cardinality-Weighted 2-Clustering Problem
189
Olga Samsonuyk, Stepan Sorokin and Maxim Staritsyn
Feedback Optimality Conditions with Weakly Invariant Functions for Nonlinear Problems of Impulsive Control
190
Oleg Zaikin and Stepan Kochemazov
Black-box optimization in an extended search space for SAT solving
194
Vladimir Dykhta and Stepan Sorokin
Feedback minimum principle for optimal control problems in discrete-time systems and its applications
197
Fedor Stonyakin, Mohammad Alkousa, Alexander Titov and Victoria Piskunova
On Some Methods for Strongly Convex Optimization Problems With One Functional Constraint
203
Dmitry Khlopin
General limit value for stationary Nash equilibrium
213
Vladimir Berikov
Semi-Supervised Classification Using Multple Clustering and Low-Rank Matrix Operations

Corresponding authors of the listed papers are invited to upload camera-ready versions of their papers through Easychair until April 7, 2019.

Please, login as a proceedings author and upload the files according to the instructions as follows:

  1. a zipped file containing all latex sources, images, and answers to the reviewers' comments; please, name this file paper-NNN.zip, where NNN is the number of your paper
  2. PDF version of your camera-ready paper
  3. scan-copy of the Copyright form, filled and signed by the corresponding author. The prefilled form you can download here.

Please note that at least one author should participate in the conference and pay the registration fee in order to have your paper included in the proceedings.


Communications in Computer and Information Science

Prefilled Copyright Form for CCIS.

Accepted papers

2
Natalia Aizenberg and Nikolai Voropai
The interaction of consumers and load serving entity to manage electricity consumption
3
Vladimir Erokhin
Regularization and matrix correction of improper linear programming problems
5
Chiang Kao
Measuring the most favorable Russell efficiency under the framework of data envelopment analysis
7
Adil Erzin and Roman Plotnikov
The Convergecast Scheduling Problem on a Regular Triangular Grid
11
Liudmila Prokudina and Dmitrii Bukharev
Simulation of flow regimes of non-isothermal liquid films
15
Elena Tabarintseva
The accuracy of approximate solutions for a boundary value inverse problem with final overdetermination
23
Polina Kononova and Igor Kulachenko
The VNS Approach for a Consistent Capacitated Vehicle Routing Problem under the Shift Length Constraints
24
Aigul Fabarisova and Vadim Kartak
An integer programming approach to the irregular polyomino tiling problem
30
Vladimir Servakh and Svetlana Malakh
The net present value maximization in inventory management system
33
Roman Plotnikov and Adil Erzin
Constructive Heuristics for Min-Power Bounded-Hops Symmetric Connectivity Problem
35
Igor Kandoba and Alexander Uspenskiy
On one applied problem of vector optimization
37
Al'Fiya Surina and Alexander Tyrsin
RISK MANAGEMENT IN GAUSSIAN STOCHASTIC SYSTEMS AS AN OPTIMIZATION PROBLEM
39
Vladimir Ushakov, Aleksandr Ershov and Maksim Pershakov
Counterexamples in the Theory of α-Sets
40
Gennady Zabudsky and Natalia Veremchuk
On the One-Dimensional Space Allocation Problem with Partial Order and Forbidden Zones
41
Evgenii Goncharov
Variable Neighborhood Search for the Resource Constrained Project Scheduling Problem
44
Viktor Ukhobotov, Konstantin Kudryavtsev and Irina Stabulit
On the problem of comparing fuzzy numbers
48
Ivan Davydov and Daniil Tolstykh
An evolution based approach for the traffic lights optimization problem
49
Ushakov Vladimir and Lebedev Pavel
Iterative methods for optimal packing approximations constructing for non convex polygons
56
Tatiana Levanova and Alexander Gnusarev
Development of Ant Colony Optimization Algorithm for Competitive p-Median Facility Location Problem with Elastic Demand
59
Igor Vasilyev, Pasquale Avella, Maurizio Boccia and Sandro Viglione
A local branching MIP heuristic for a real-world Curriculum-Based Course Timetabling Problem
60
Alexander Kelmanov and Vladimir Khandeev
The problem K-means and given J-centers: polynomial solvability in one dimension
63
Inna Urazova, Ruslan Simanchev and Yury Kochetov
Polyhedral attack on the graph approximation problem
64
Leonid Popov
Methods for matrix games with mixed strategies and quantile payoff function
67
Lev Petrov
Using Nonlinear Interactions To Control Oscillations Of Dynamic Systems
71
Artem Ripatti and Vadim Kartak
Bounds for non-IRUP instances of Cutting Stock Problem with minimal capacity
72
Evgeni Nurminski and Natalia Shamray
Discrete Time Lyapunov-Type Convergence Conditions for Recursive Sequences in Optimization
80
Artyom Makovetskii, Sergei Voronin, Vitaly Kober and Aleksei Voronin
A generalized point-to-point approach for orthogonal transformations
81
Robert Namm and Georgiy Tsoy
A modified duality scheme for solving 3D elastic problem with a crack
83
Alexander Chentsov, Alexey Grigoryev and Alexey Chentsov
Procedures of local optimization in routing problems with constraints
99
Lidia Zaozerskaya
Analysis of Integer Programming Model of Academic Load Distribution
111
Alexander Semenov
Merging variables: one technique of search in pseudo-Boolean optimization
114
Timur Merembayev, Yedilkhan Amirgaliyev, Shahriar Shamiluulu and Didar Yedilkhan
Using machine learning algorithm for diagnosis of stomach disorders
116
Eugeniia Markova and Inna Sidler
Optimization problem in an integral model of developing system without prehistory
126
Igor Bykadorov
Social Optimality in International Trade under Monopolistic Competition
131
Anna Lempert, Alexander Kazakov and Quang Mung Le
On the Thinnest Covering of Fixed Size Containers with Non-Euclidean Metric by Incongruent Circles
148
Evgeniy A. Krupennikov
On estimates of the solutions of inverse problems of optimal control
150
Aleksandr Buldaev and Ivan Burlakov
Iterative Method with Exact Fulfillment of Constraints in Optimal Control Problems
154
Guzel Sharipzhanovna Shkaberina, Viktor Ivanovich Orlov, Elena Mikhailovna Tovbis and Lev Aleksandrovich Kazakovtsev
Identification of the Optimal Set of Informative Features for the Problem of Separating a Mixed Production Batch of Semiconductor Devices for the Space Industry
164
Yuri Kan and Sofia Vasil'Eva
Deterministic approximation of stochastic programming problems with probabilistic constraints
183
Anastasia Tavaeva, Dmitry Kurennov, Vladimir Krotov and Alexander Petunin
A Cost Minimizing at Laser Cutting of Sheet Parts on CNC machines
200
Anton Ushakov and Igor Vasilyev
A computational comparison of parallel and distributed k-median clustering algorithms on large-scale image data
205
Ovanes Petrosian and Anna Tur
Hamilton-Jacobi-Bellman Equations for Non-cooperative Differential Games with Continuous Updating
209
Olga Murav'Eva
Matrix Correction of Inconsistent Systems of Linear Inequalities Using the Matrix l1 Norm
216
Edward Kh. Gimadi and Ekaterina Shin
On random MST problem with given diameter
222
Hanan Shabana and Mikhail Volkov
Using Sat solvers for synchronization issues in partial deterministic automata
229
Aleksander Gornov, Tatiana Zarodnyuk, Anton Anikin and Pavel Sorokovikov
The Stochastic Coverings Algorithm for Solving Applied Optimal Control Problems

Corresponding authors of the listed papers are invited to upload camera-ready versions of their papers through Easychair until June 30, 2019.

Please, login as a proceedings author and upload the files according to the instructions as follows:

  1. a zipped file containing all latex sources, images, and answers to the reviewers' comments; please, name this file paper-NNN.zip, where NNN is the number of your paper
  2. PDF version of your camera-ready paper
  3. scan-copy of the Copyright form, filled and signed by the corresponding author. The prefilled form you can download here.

Please note that at least one author should participate in the conference and pay the registration fee in order to have your paper included in the proceedings.



Специальные выпуски журналов

Papers significantly extending the results presented at the conference MOTOR 2019, or related papers, will be considered for peer-reviewed publication in special issues of the following journals:


Impact Factor "1.631"

Journal of Global Optimization

Журнал индексируется в WoS (IF=1.631, Q1) и Scopus (Q1 JSR). Уровень и тематика принимаемых к опубликованию работ (см. здесь) соответствует самым высоким мировым стандартам. Срок отсылки работ в спецвыпуск - 1 ноября 2019. Редакция обращается с просьбой к авторам при подготовке и оформлении статей придерживаться следующих требований (см. здесь). Отсылка рукописей статей производится через онлайн-систему журнала. При отсылке, пожалуйста, указывайте код специального выпуска “SI: MOTOR-19”.
Приглашенные редакторы:
Проф. Панос М. Пардалос - Университет Флориды, США
Проф. М.Ю. Хачай - Институт математики и механики им Н.Н.Красовского УрО РАН
Проф. Ю.А. Кочетов - Институт математики им С.Л.Соболева СО РАН


2018 Impact Factor "1.336"

Optimization Methods & Software (OMS)

Статьи, посвященные существенному развитию результатов, обсуждавшихся на конференции, а также по близкой тематике, могут быть представлены к публикации в специальном выпуске журнала 'Optimization Methods and Software (OMS)'. (WoS, IF=1.336, ежегодно лучшие статьи участвуют в конкурсе на присуждение премии им. Чарльза Бройдена). Срок отсылки работ: 1 ноября 2019. Требования к уровню и тематике статей, стилеые файлы и инструкции для авторов здесь. Пожалуйста, используйте для отсылки рукописей систему ScholarOne Manuscripts. Код спецвыпуска "MOTOR19".
Приглашенные редакторы:
Проф. О.В. Хамисов - Институт систем энергетики им. Л.А. Мелентьева РАН, Россия
Проф. А.В. Еремеев - Институт математики им. С.Л. Соболева РАН, Россия
Чл-корр. РАН В.Н. Ушаков - Институт математики и механики им. Н.Н.Красовского УрО РАН, Россия


Yugoslav Journal of Operations Research (YuJOR)

YuJOR - Югославский журнал исследования операций - международный журнал, посвященный широкому кругу вопросов в области исследования операций, наук о системах, теории управления и математической экономики. YuJOR принимает к опубликованию рецензируемые работы, содержащие значительные результаты в перечисленных областях, как теоретические, так и эмпирические или описательные. Журнал индексируется Scopus (Q3 JSR). В специальный выпуск приглашаются статьи, не превышающие по объему 23 стр. и оформленные в системе LaTeX в соответствии с правилами и шаблонами. Срок отсылки статей - 1 ноября 2019. Пожалуйста, при отсылке рукописи, используйте код специального выпуска "MOTOR 2019".
Приглашенные редакторы:
Проф. Л.А. Петросян - Санкт-Петербургский государственный университет
Проф. А.А. Петунин - Уральский федеральный университет
Проф. В.М. Картак - Уфимский государственный авиационный технический университет


Дискретный анализ и исследование операций

Журнал издается в Институте математики им. С.Л. Соболева СО РАН. В журнал принимаются оригинальные статьи на русском и английском языках, содержащие теоретические результаты в области дискретного анализа и исследования операций, а также статьи прикладной направленности. Переводы статей на английский язык публикуются в журнале Journal of Applied and Industrial Mathematics, индексируемом в Scopus (Q2, JSR 0,292). В специальный выпуск приглашаются статьи, не превышающие по объему 20–25 стр. и оформленные в системе LaTeX в соответствии с правилами. Срок отсылки статей – 1 ноября 2019. Адрес редакции: discopr@math.nsc.ru. Пожалуйста, при отсылке рукописи используйте код специального выпуска "MOTOR 2019".
Приглашенные редакторы:
Проф. Е.А. Нурминский - Дальневосточный федеральный университет



Submission dates and instructions

February 1
Up to this date, we ask to register your talk using easychair conference account. This task is quite simple. The corresponding author is invited to log on to easychair, start a new submission and fill a form pointing out submission title, authors’ names, keywords and a short abstract in a plain text.
February 15
Up to this date, corresponding authors have an opportunity to edit all the information and upload (re-upload) their papers for possible inclusion to the conference proceedings, which will be published by Springer as volumes of LNCS and CCIS series
November 1
Up to this date, all the authors are invited to submit their significantly elaborated papers presented on the conference or some another related papers to special issues of the peer-reviewed journals
Note: full paper submission is not a necessary condition for participating in MOTOR 2019. To give a talk, it is sufficient to register it in easychair.

РЕГИСТРАЦИОННЫЕ ВЗНОСЫ

до 1 мая 2019
после 2 мая
Для студентов и аспирантов
3500 руб.
4000 руб.
Для остальных участников
7000 руб.
8000 руб.

Регистрационный взнос подразумевает участие в пленарных и секционных заседаниях, круглых столах, а также организованный трансфер (из ИММ УрО РАН в санаторий Обуховский и обратно) и комплект участника. Для публикации статьи, принятой в LNCS или CCIS, необходима регистрация хотя бы одного из соавторов.

Способы оплаты: на счет соорганизатора конференции ООО «Визит Урал-Сибирь», кредитной картой или наличными по прибытии на конференцию

Процедура регистрации: для регистрации, пожалуйста, отправьте по адресу motor2019.registr@gmail.com письмо с темой "MOTOR 2019 Registration Form", содержащее заполненную регистрационную форму. В ответном письме, которое поступит в течение 3 рабочих дней, вы получите исчерпывающие инструкции по оплате регистрационного взноса.

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  4. Гражданство
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Программа конференции




Техническая программа

Расписание

Место проведения конференции

Конференция будет проводиться в санатории «Обуховский» (https://www.obuhovski.com), расположенном в живописном месте недалеко от города Екатеринбурга, находящегося на границе Европы и Азии. Оргкомитет предварительно зарезервировал для участников конференции комфортабельные одно- и двухместные номера с корпоративной скидкой, включающей одиночное или совместное проживание, трехразоваое питание, оздоровительную программу (минеральная вода, посещение бассейна с минеральной водой, спортивные мероприятия и пр.).

Карта санатория «Обуховский»

Стоимость размещения в зарезервированных номерах (при бронировании до 26 мая)

Вид размещения
Срок оплаты
Цена за ночь (руб.)
Количество ночей
Общая стоимость (руб.)
Одноместное размещение
(в 1 или 2-местном номере)
до 20 мая 2019
2800
5
14000
Место в двухместном
номере
до 20 мая 2019
2550
5
12750
Одноместное размещение
(в 1 или 2-местном номере)
после 20 мая 2019
3200
5
16000
Место в двухместном
номере
после 20 мая 2019
2800
5
14000

Просим вас учесть, что число предварительно зарезервированных номеров ограничено. Дополнительные номера (в том числе, более высокого класса) могут быть забронированы участником самостоятельно по ценам санатория (https://www.obuhovski.com/prajs-list/).

Порядок бронирования и оплаты:

  1. участник обращается с Заявкой-письмом о выставлении Счёта на оплату забронированного места на почту (eni.obuhovski@mail.ru). Просим привести в заявке следующую информацию: ФИО, дату и примерное время заселения, дату и время отъезда, вид размещения (одноместное или двухместное (просьба указать ФИО предполагаемого соседа)), номер телефона для обратной связи и электронный адрес для отправки Счёта;
  2. ответное письмо будет содержать счёт и реквизиты для оплаты;
  3. участник оплачивает проживание по выставленному Счету и высылает копию квитанции по адресу: motor2019.registr@gmail.com;
  4. просим Вас сохранить документы об оплате и предъявить их при поселении;
  5. по просьбе участника во время пребывания в санатории будут подготовлены все необходимые финансовые документы (договор, акт, квитанция и т.п.).

Обзорная экскурсия

Уважаемые участники конференции, в среду 10 июля состоится обзорная экскурсия по Екатеринбургу с заездом на мемориал «Европа-Азия», посещением геологического музея и обедом в ресторане русской кухни.


Уральский геологический музей при Уральском государственном горном университете был открыт в 1937 году. В нём хранится более 40 тысяч экспонатов, представляющих минералы, полезные ископаемые, породы и палеонтологические находки Уральского региона.


Обед запланирован в ресторане русской кухни «Подкова», расположенном в самом центре Екатеринбурга по адресу проспект Ленина, 28/2, меню во вложении.


Время выезда: 10.00. Продолжительность: 6 - 7 часов. Стоимость экскурсии 2000р. Количество мест ограничено, просьба до 1 июля подать заявку на участие в экскурсии на почту конференции motor2019.registr@gmail.com.

Как добраться

Зарегистрированным участникам конференции будет предложен коллективный трансфер:
 12 июля 2019 г., в 14:00, от санатория «Обуховский» до аэропорта Кольцово и ИММ УрО РАН

Ежедневно, с 8 по 11 июля будут организованы рейсы микроавтобуса:
 8:00 — от здания ИММ УрО РАН в сан. «Обуховский»
 19:00 — от сан. «Обуховский» до ИММ УрО РАН

Время местное (Екатеринбург, GMT+5).
Контактная информация сан. «Обуховский».