ESAIM - Control, Optimisation and Calculus of Variations

SJR Rank #6,341H-index: 72SJR: 0.847Best quartile: Q1
Journal website: aims, scope and author guidelines
Publisher

EDP Sciences

Country

France

Type

journal

SJR by Edition

2022202500.250.50.751

Subject Categories

  • Computational MathematicsQ1
  • Control and OptimizationQ1
  • Control and Systems EngineeringQ2

Areas: Engineering · Mathematics

Most published research topics

Advanced Mathematical Modeling in EngineeringStability and Controllability of Differential EquationsNonlinear Partial Differential EquationsNumerical methods in inverse problemsOptimization and Variational AnalysisGeometric Analysis and Curvature FlowsStochastic processes and financial applicationsAdvanced Mathematical Physics ProblemsAdvanced Numerical Methods in Computational MathematicsContact Mechanics and Variational Inequalities

Source: OpenAlex

Publication Statistics

2025 Docs3-Year DocsCitable Docs070140210280

Documents per Year

202220250306090120

Detailed Information

ISSN

1262-3377, 1292-8119

SJR Best Quartile

Q1

Region

Western Europe

Citations per Document (2 years)

1.36

References per Document

37.69

Coverage

1996-2026

Scope

ESAIM: COCV strives to publish rapidly and efficiently papers and surveys in the areas of Control, Optimisation and Calculus of Variations. Articles may be theoretical, computational, or both, and they will cover contemporary subjects with impact in forefront technology, biosciences, materials science, computer vision, continuum physics, decision sciences and other allied disciplines. Targeted topics include: in control: modeling, controllability, optimal control, stabilization, control design, hybrid control, robustness analysis, numerical and computational methods for control, stochastic or deterministic, continuous or discrete control systems, finite-dimensional or infinite-dimensional control systems, geometric control, quantum control, game theory; in optimisation: mathematical programming, large scale systems, stochastic optimisation, combinatorial optimisation, shape optimisation, convex or nonsmooth optimisation, inverse problems, interior point methods, duality methods, numerical methods, convergence and complexity, global optimisation, optimisation and dynamical systems, optimal transport, machine learning, image or signal analysis; in calculus of variations: variational methods for differential equations and Hamiltonian systems, variational inequalities; semicontinuity and convergence, existence and regularity of minimizers and critical points of functionals, relaxation; geometric problems and the use and development of geometric measure theory tools; problems involving randomness; viscosity solutions; numerical methods; homogenization, multiscale and singular perturbation problems.

Metrics from SCImago Journal Rank 2025. View on SCImago