Variational models of robust optimal transport

TL;DR

This paper develops two variational models for robust optimal transport networks that are resilient to damages, balancing costs and functionality, with proofs of minimizer existence and comparative analysis.

Contribution

It introduces Eulerian and Lagrangian variational formulations for robust optimal transport, expanding modeling capabilities for network resilience.

Findings

Existence of minimizers proven for both models.

Eulerian model requires unoriented networks for existence.

Lagrangian model handles general damages but needs positive distance between source and target.

Abstract

This paper introduces two variational formulations for a model of robust optimal transport, that is, the problem of designing optimal transport networks that are resilient to potential damages, balancing construction costs against the benefit of maintaining partial functionality when parts of the network are damaged. We propose a Eulerian formulation, where the network is modeled by a rectifiable measure and recovery plans are represented by 1-dimensional normal currents. This framework allows for changes in the direction of the transportation in response to damages but restricts damages to be characteristic functions of closed sets. We also propose a Lagrangian formulation, where the network is a traffic plan (that is, a measure on the space of Lipschitz curves) and recovery plans are sub-traffic plans. This approach prescribes the network's orientation but allows for a wider class of damages. We prove existence of minimizers in both settings. The two models are compared through examples that illustrate their main differences: the Eulerian formulation's necessity for an unoriented network to achieve existence, the Lagrangian formulation's ability to handle general damages and its requirement for a positive distance between the supports of the source and target measures.