ESAIM-CONTROL OPTIMISATION AND CALCULUS OF VARIATIONS SCIE

中文简介

ESAIM: COCV致力于在控制、优化和变异计算领域快速有效地发表论文和调查。文章可以是理论性的，计算性的，或者两者都有，它们将涵盖前沿技术、生物科学、材料科学、计算机视觉、连续物理、决策科学和其他相关学科的影响的当代主题。有针对性的主题包括:控制:建模、可控性、最优控制、稳定、控制设计、混合控制、鲁棒性分析、控制的数值和计算方法、随机或确定性、连续或离散控制系统、有限维或无限维控制系统、几何控制、量子控制、博弈论;优化:数学规划、大型系统、随机优化、组合优化、形状优化、凸或非光滑优化、反问题、内点法、对偶法、数值方法、收敛与复杂性、全局优化、优化与动力系统、最优传输、机器学习、图像或信号分析;变分学:微分方程和哈密顿系统的变分方法，变分不等式;半连续性与收敛、极小化器的存在性与正则性、泛函的临界点、松弛性几何问题与几何测度理论工具的使用与发展涉及随机性的问题;粘度的解决方案;数值方法;均匀化、多尺度和奇异摄动问题。

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英文简介

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.