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MOTOR 2021

 

International conference “Mathematical Optimization Theory and Operations Research(MOTOR 2021) will be held on July 5-10, 2021, in the picturesque place not far from Irkutsk (Russia) and Lake Baikal.

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.

 

MOTOR 2021 is a successor of the following well-known International and All-Russian conference series, which were held in Ural, Siberia, and the Far East for a long time:

  • Baikal International Triennial School Seminar on Methods of Optimization and Their Applications (Irkutsk, Ulan-Ude),
    last event
    http://isem.irk.ru/conferences/mopt2017/en/index.html

  • Mathematical Programming and Applications (Ekaterinburg), last event http://mpa.imm.uran.ru/96/en

  • Discrete Optimization and Operations Research (Novosibirsk, Vladivostok), last event  http://www.math.nsc.ru/conference/door/2016/ 

  • Optimization Problems and their Applications (Omsk), last event http://opta18.oscsbras.ru/en/

The previous MOTOR conferences:

  • Mathematical Optimization Theory and Operations Research  (MOTOR 2019) (Ekaterinburg)  http://motor2019.uran.ru/

  • Mathematical Optimization Theory and Operations Research  (MOTOR 2020) (Online) http://www.math.nsc.ru/conference/motor/2020/

 

Main topics

The main conference topics include, but not limited to

  • theory and methods of mathematical optimization

  • integer programming and combinatorial optimization

  • global optimization, stochastic integer programming, multi-objective programming

  • computational complexity, approximation algorithms, schemes, bounds, heuristics and metaheuristics

  • optimal control and game theory

  • mathematical economics and multilevel programming

  • optimization and approximation

  • optimization in machine learning and data analysis

  • applications in operations research: scheduling, routing, facility location, packing and cutting, manufacturing systems, etc.