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The optimal (Monge-Kantorovich) transportation problem is discussed from several points of view. The Lagrangian formulation extends the action of the {\em Lagrangian} $L(v,x,t)$ from the set of orbits in $\R^n$ to a set of measure-valued…

Mathematical Physics · Physics 2007-05-23 Gershon Wolansky

We prove existence of an optimal transport map in the Monge-Kantorovich problem associated to a cost $c(x,y)$ which is not finite everywhere, but coincides with $|x-y|^2$ if the displacement $y-x$ belongs to a given convex set $C$ and it is…

Optimization and Control · Mathematics 2011-10-17 Chloé Jimenez , Filippo Santambrogio

We rephrase Monge's optimal transportation (OT) problem with quadratic cost--via a Monge-Amp\`ere equation--as an infinite-dimensional optimization problem, which is in fact a convex problem when the target is a log-concave measure with…

Numerical Analysis · Mathematics 2017-08-29 Michael Lindsey , Yanir A. Rubinstein

Consider the problem of optimally matching two measures on the circle, or equivalently two periodic measures on the real line, and suppose the cost of matching two points satisfies the Monge condition. We introduce a notion of locally…

Optimization and Control · Mathematics 2010-05-04 Julie Delon , Julien Salomon , Andrei Sobolevskii

We consider the optimal transport problem over convex costs arising from optimal control of linear time-invariant(LTI) systems when the initial and target measures are assumed to be supported on the set of equilibrium points of the LTI…

Optimization and Control · Mathematics 2023-12-19 Karthik Elamvazhuthi , Matt Jacobs

We consider the Monge problem of optimal transport between a compactly supported source measure and a target probability measure with unbounded support. We consider the convergence of optimal maps and potential functions when the target…

Numerical Analysis · Mathematics 2026-03-03 Axel G. R. Turnquist

We study the optimal transport problem in the Euclidean space where the cost function is given by the value function associated with a Linear Quadratic minimization problem. Under appropriate assumptions, we generalize Brenier's Theorem…

Optimization and Control · Mathematics 2011-05-23 Ahed Hindawi , Ludovic Rifford , Jean-Baptiste Pomet

The classical problem of optimal transportation can be formulated as a linear optimization problem on a convex domain: among all joint measures with fixed marginals find the optimal one, where optimality is measured against a cost function.…

Optimization and Control · Mathematics 2012-11-29 Jonathan Korman , Robert J. McCann

We study Monge's optimal transportation problem, where the cost is given by optimal control cost. We prove the existence and uniqueness of an optimal map under certain regularity conditions on the Lagrangian, absolute continuity of the…

Optimization and Control · Mathematics 2007-11-24 Andrei Agrachev , Paul Lee

Inspired by the matching of supply to demand in logistical problems, the optimal transport (or Monge--Kantorovich) problem involves the matching of probability distributions defined over a geometric domain such as a surface or manifold. In…

Optimization and Control · Mathematics 2018-05-02 Justin Solomon

This paper deals with the existence of optimal transport maps for some optimal transport problems with a convex but non strictly convex cost. We give a decomposition strategy to address this issue. As part of our strategy, we have to treat…

Classical Analysis and ODEs · Mathematics 2009-09-16 Guillaume Carlier , Luigi De Pascale , Filippo Santambrogio

We establish numerical methods for solving the martingale optimal transport problem (MOT) - a version of the classical optimal transport with an additional martingale constraint on transport's dynamics. We prove that the MOT value can be…

Probability · Mathematics 2019-04-08 Gaoyue Guo , Jan Obloj

In this paper, we study the optimal transportation for generalized Lagrangian $L=L(x, u,t)$, and consider the cost function as following: $$c(x, y)=\inf_{\substack{x(0)=x\\x(1)=y\\u\in\mathcal{U}}}\int_0^1L(x(s), u(x(s),s), s)ds.$$ Where…

Dynamical Systems · Mathematics 2013-12-03 Ji Li , Jianlu Zhang

We develop an $\e$-regularity theory at the boundary for a general class of Monge-Amp\`ere type equations arising in optimal transportation. As a corollary we deduce that optimal transport maps between H\"older densities supported on $C^2$…

Analysis of PDEs · Mathematics 2014-12-19 Shibing Chen , Alessio Figalli

We study the vanishing-regularization limit of entropically regularized optimal transport (EOT) for the Euclidean distance cost $c(x,y)=\|x-y\|$ in dimension $d>1$. We develop a comprehensive variational convergence framework that entails…

Optimization and Control · Mathematics 2026-04-29 Marcel Nutz , Chenyang Zhong

We introduce and analyze a statistical estimator for Monge transport maps: solutions to the quadratic optimal transport problem in Euclidean space. For absolutely continuous source measures, this map is uniquely defined as the gradient of a…

Optimization and Control · Mathematics 2026-04-27 Elsa Cazelles , Edouard Pauwels , Léo Portales

Optimal maps, solutions to the optimal transportation problems, are completely determined by the corresponding c-convex potential functions. In this paper, we give simple sufficient conditions for a smooth function to be c-convex when the…

Differential Geometry · Mathematics 2010-06-22 Paul W. Y. Lee

Finding optimal trajectories for multiple traffic demands in a congested network is a challenging task. Optimal transport theory is a principled approach that has been used successfully to study various transportation problems. Its usage is…

Physics and Society · Physics 2024-10-10 Abdullahi Adinoyi Ibrahim , Michael Muehlebach , Caterina De Bacco

We address the Monge problem in metric spaces with a geodesic distance: (X, d) is a Polish space and dN is a geodesic Borel distance which makes (X,dN) a possibly branching geodesic space. We show that under some assumptions on the…

Probability · Mathematics 2012-10-01 Fabio Cavalletti

Optimal transport (OT) theory has been been used in machine learning to study and characterize maps that can push-forward efficiently a probability measure onto another. Recent works have drawn inspiration from Brenier's theorem, which…

Machine Learning · Computer Science 2023-02-13 Théo Uscidda , Marco Cuturi
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