MOTOR 2026
International conference “Mathematical Optimization Theory and Operations Research” (MOTOR 2026) will be held on July 6-11, 2026, 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 2026 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
- Mathematical Programming and Applications (Ekaterinburg), last event
- Discrete Optimization and Operations Research (Novosibirsk, Vladivostok), last event
- Optimization Problems and their Applications (Omsk), last event
The previous MOTOR conferences:
Dates | Venue | Proceedings | ||||||
| MOTOR 2025 | July 7–11, 2025 | Novosibirsk, Russia | LNCS Vol. 15681 | Proceedings of IMM of UB RAS Vol. 31, issue 3 | ||||
| MOTOR 2024 | June 30 – July 8, 2024 | Omsk, Russia | LNCS Vol. 14766 | CCIS Vol. 2239 | ||||
| MOTOR 2023 | July 2–8, 2023 | Ekaterinburg, Russia | LNCS Vol. 13930 | CCIS Vol. 1881 | ||||
| MOTOR 2022 | July 2–6, 2022 | Petrozavodsk, Russia | LNCS Vol. 13367 | CCIS Vol. 1661 | ||||
| MOTOR 2021 | July 5–10, 2021 | Irkutsk-Baikal, Russia | LNCS Vol. 12755 | CCIS Vol. 1476 | ||||
| MOTOR 2020 | July 6–10, 2020 | Novosibirsk (online), Russia | LNCS Vol. 12095 | CCIS Vol. 1275 | ||||
| MOTOR 2019 | July 8–12, 2019 | Ekaterinburg, Russia | LNCS Vol. 11548 | CCIS Vol. 1090 | ||||
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.
