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We introduce and prove convergence of a damped Newton algorithm to approximate solutions of the semi-discrete optimal transport problem with storage fees, corresponding to a problem with hard capacity constraints. This is a variant of the…

Numerical Analysis · Mathematics 2020-08-17 Mohit Bansil , Jun Kitagawa

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 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

In this paper, we propose a novel neural network framework, the Legendre-Kolmogorov-Arnold Network (Legendre-KAN) method, designed to solve fully nonlinear Monge-Amp\`ere equations with Dirichlet boundary conditions. The architecture…

Numerical Analysis · Mathematics 2025-04-08 Bingcheng Hu , Lixiang Jin , Zhaoxiang Li

This paper studies the equitable and optimal transport (EOT) problem, which has many applications such as fair division problems and optimal transport with multiple agents etc. In the discrete distributions case, the EOT problem can be…

Optimization and Control · Mathematics 2021-10-04 Minhui Huang , Shiqian Ma , Lifeng Lai

We study the estimation of optimal transport (OT) maps between an arbitrary source probability measure and a log-concave target probability measure. Our contributions are twofold. First, we propose a new evolution equation in the set of…

Optimization and Control · Mathematics 2026-04-13 Théo Dumont , Théo Lacombe , François-Xavier Vialard

Optimal transport (OT) provides effective tools for comparing and mapping probability measures. We propose to leverage the flexibility of neural networks to learn an approximate optimal transport map. More precisely, we present a new and…

Machine Learning · Computer Science 2022-07-06 Florentin Coeurdoux , Nicolas Dobigeon , Pierre Chainais

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 introduce an efficient computational framework for solving a class of multi-marginal martingale optimal transport problems, which includes many robust pricing problems of large financial interest. Such problems are typically…

Computational Finance · Quantitative Finance 2025-03-21 Linn Engström , Sigrid Källblad , Johan Karlsson

As more and more numerical and analytical solutions to the linear neutron transport equation become available, verification of numerical results is increasingly important. This presentation concerns the development of another benchmark for…

Computational Physics · Physics 2024-06-21 Barry Ganapol

This work is concerned with the efficient optimization method for solving a large class of optimal mass transport problems. An inexact primal-dual algorithm is presented from the time discretization of a proper dynamical system, and by…

Optimization and Control · Mathematics 2022-07-29 Jun Hu , Hao Luo , Zihang Zhang

In this paper, we prove the existence of classical solutions to second boundary value prob- lems for generated prescribed Jacobian equations, as recently developed by the second author, thereby obtaining extensions of classical solvability…

Analysis of PDEs · Mathematics 2018-02-14 Feida Jiang , Neil S. Trudinger

In this work, the authors address the Optimal Transport (OT) problem on graphs using a proximal stabilized Interior Point Method (IPM). In particular, strongly leveraging on the induced primal-dual regularization, the authors propose to…

Optimization and Control · Mathematics 2023-07-12 Stefano Cipolla , Jacek Gondzio , Filippo Zanetti

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 propose a numerical method for solving the multi-marginal Monge problem, which extends the classical Monge formulation to settings involving multiple target distributions. Our approach is based on the Hilbert space embedding of…

Optimization and Control · Mathematics 2025-07-15 Yumiharu Nakano , Takafumi Saito

In this paper, we study a spline collocation method for a numerical solution to the optimal transport problem We mainly solve the \MAE with the second boundary condition numerically by proposing a center matching algorithm. We prove a…

Numerical Analysis · Mathematics 2023-10-27 Ming-Jun Lai , Jinsil Lee

An adaptive, adversarial methodology is developed for the optimal transport problem between two distributions $\mu$ and $\nu$, known only through a finite set of independent samples $(x_i)_{i=1..N}$ and $(y_j)_{j=1..M}$. The methodology…

Optimization and Control · Mathematics 2019-02-20 Montacer Essid , Debra Laefer , Esteban G. Tabak

In the first part of the paper we briefly decribe the classical problem, raised by Monge in 1781, of optimal transportation of mass. We discuss also Kantorovich's weak solution of the problem, which leads to general existence results, to a…

Analysis of PDEs · Mathematics 2007-05-23 Luigi Ambrosio

We present a flow-based approach to the optimal transport (OT) problem between two continuous distributions $\pi_0,\pi_1$ on $\mathbb{R}^d$, of minimizing a transport cost $\mathbb{E}[c(X_1-X_0)]$ in the set of couplings $(X_0,X_1)$ whose…

Machine Learning · Statistics 2022-09-30 Qiang Liu

We investigate the approximation of the Monge problem (minimizing \int\_$\Omega$ |T (x) -- x| d$\mu$(x) among the vector-valued maps T with prescribed image measure T \# $\mu$) by adding a vanishing Dirichlet energy, namely $\epsilon$…

Optimization and Control · Mathematics 2017-01-05 Luigi De Pascale , Jean Louet , Filippo Santambrogio