Conference Information

MOTOR 2019: International Conference on Mathematical Optimization Theory and Operations Research

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Submission Date:
2019-02-01 Extended
Notification Date:
2019-03-15
Conference Date:
2019-07-08
Location:
Ekaterinburg, Russian
Viewed: 15721   Tracked: 0   Attend: 0

Conference Partner Index (CP-I)

42.1 / 100
Ranked #4,082 of 5,650 conferences · Top 73%

#117 of 138 in Theory & Algorithms

Limited evidence: this conference is not listed in CCF / ICORE / QUALIS and has no acceptance-rate data on file, so most of the score falls back to the neutral baseline.
Academic recognition (35%) No data - scored at the neutral baseline of 50 —
Submission selectivity (20%) No data - scored at the neutral baseline of 50 —
Editions held (20%) No data - scored at the neutral baseline of 50 —
Community attention (10%)
8
Public record completeness (15%)
25

Inputs used: Researchers who opened this page in the past 24 months: 2

Missing from the public record: Historical acceptance rates (+4.5) · Past editions (+3.0) · Best-paper records (+2.3)
Organizers can add these from this page after claiming the conference; scores are recomputed nightly. How to raise this score

Confidence 25% - the share of the score backed by observed data rather than the neutral baseline. How this score is calculated · Browse the ranking · Algorithm version 1.1 · Computed 2026-09-06

Call For Papers

MOTOR 2019 (International Conference on Mathematical Optimization Theory and Operations Research) is an academic conference held in Ekaterinburg, Russian on 2019-07-08. The paper submission deadline is 2019-02-01 (extended). Acceptance notifications are sent on 2019-03-15.

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. MAIN TOPICS 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.
Last updated by Dou Sun on

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