ABOUT THE CONFERENCE
International conference “Mathematical Optimization Theory and Operations Research” (MOTOR2019) http://motor2019.uran.ru will be held on July 8-12, 2019, in a picturesque place near Ekaterinburg, Russia, at the borderline between Europe and Asia.
The conference brings together a wide research community in the fields of mathematical programming and global optimization, discrete optimization, complexity theory and combinatorial algorithms, optimal control and games, and their applications in relevant practical problems of operations research, mathematical economy, and data analysis.
February 1, 2019
February 15, 2019
Call for papers:
MOTOR2019 is a descendant of a number of well-known International and All-Russian conferences, which were held in Ural, Siberia, and the Far East for a long time:
# in series
Baikal International Triennial School Seminar on Methods of Optimization and Their Applications, BITSS MOPT
Mathematical Programming and Applications, MPA
Discrete Optimization and Operations Research, DOOR
Optimization Problems and their Applications, OPTA
- mathematical programming
- global optimization
- integer programming and combinatorial optimization
- computational complexity, approximation algorithms, schemes, bounds, heuristics and metaheuristics
- optimal control and game theory
- optimization and approximation
- optimization in machine learning and data analysis
- applications in operations research: scheduling, routing, facility location, packing and cutting, manufacturing systems, etc.
Program Committee Chairs
(to be extended)
Industry session chairs
Prof. Olga Battaia
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.
Prof. Christoph Dürr
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.
Prof. Alexander Grigoriev
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.
Prof. Mikhail Kovalyov
United Institute of Informatics Problems NASB
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.
Prof. Vadim Levit
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.
Prof. Bertrand M.T. Lin
National Chiao Tung University, Hsinchu
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.
Prof. Angelo Sifaleras
University of Macedonia
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.
Prof. Vitaly Strusevich
University of Greenwich
Design of Fully-Polynomial 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.
Prof. Natalia Shakhlevich
University of Leeds
Authors are invited 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. Please, follow the official Springer authors guidelines and LNCS Latex templates. All papers should be submitted through the easychair conference management system, which is available now.
Publication and Special Issues
Conference proceedings will be published by Springer Nature as volumes of Lecture Notes in Computer Science (LNCS) and Communications in Computer and Information Science (CCIS) series.