江苏省应用数学（中国矿业大学）中心系列学术报告
报告题目：An efficient augmented Lagrangian method for dynamic optimal transport based on second-order cone programming
报告人：陈亮 副教授（湖南大学）
报告时间：2026/04/28 14:30
报告地点：腾讯会议465-593-316
摘 要：This talk introduces an efficient numerical approach to solve dynamic optimal transport (DOT) problems with quadratic cost in Euclidean spaces (using staggered grid discretization) or on surfaces (using a triangular mesh for space together with a staggered grid for time). Building on the convex DOT model of Benamou and Brenier, we reformulate the discretized dual DOT problem to a linear second-order cone programming (SOCP) problem. Then, by taking advantage of the SOCP reformulation, we can solve them efficiently by a computationally highly economical implementation of an inexact symmetric Gauss-Seidel decomposition-based proximal augmented Lagrangian method, which converges to a Karush-Kuhn-Tucker solution without any additional assumptions. Implemented as open-source software packages, the proposed approach demonstrates robustness, effectiveness, and superior computational efficiency in extensive numerical experiments on various datasets, achieving a several-fold speed-up over the state-of-the-art solvers.