Recently a Dynamic-Monge-Kantorovich formulation of the PDE-based [Formula presented]-optimal transport problem was presented. The model considers a diffusion equation enforcing the balance of the transported masses with a time-varying conductivity that evolves proportionally to the transported flux. In this paper we present an extension of this model that considers a time derivative of the conductivity that grows as a power-law of the transport flux with exponent β>0. A sub-linear growth (0<1) penalizes the flux intensity and promotes distributed transport, with equilibrium solutions that are reminiscent of Congested Transport Problems. On the contrary, a super-linear growth (β>1) favors flux intensity and promotes concentrated transport, leading to the emergence of steady-state “singular” and “fractal-like” configurations that resemble those of Branched Transport Problems. We derive a numerical discretization of the proposed model that is accurate, efficient, and robust for a wide range of scenarios. For β>1 the numerical model is able to reproduce highly irregular and fractal-like formations without any a-priory structural assumption.
Recently a Dynamic-Monge-Kantorovich formulation of the PDE-based [Formula presented]-optimal transport problem was presented. The model considers a diffusion equation enforcing the balance of the transported masses with a time-varying conductivity that evolves proportionally to the transported flux. In this paper we present an extension of this model that considers a time derivative of the conductivity that grows as a power-law of the transport flux with exponent β>0. A sub-linear growth (0<β<1) penalizes the flux intensity and promotes distributed transport, with equilibrium solutions that are reminiscent of Congested Transport Problems. On the contrary, a super-linear growth (β>1) favors flux intensity and promotes concentrated transport, leading to the emergence of steady-state “singular” and “fractal-like” configurations that resemble those of Branched Transport Problems. We derive a numerical discretization of the proposed model that is accurate, efficient, and robust for a wide range of scenarios. For β>1 the numerical model is able to reproduce highly irregular and fractal-like formations without any a-priory structural assumption.
Recently a Dynamic-Monge-Kantorovich formulation of the PDE-based Image 1-optimal transport problem was presented. The model considers a diffusion equation enforcing the balance of the transported masses with a time-varying conductivity that evolves proportionally to the transported flux. In this paper we present an extension of this model that considers a time derivative of the conductivity that grows as a power-law of the transport flux with exponent β>0. A sub-linear growth (0<β<1) penalizes the flux intensity and promotes distributed transport, with equilibrium solutions that are reminiscent of Congested Transport Problems. On the contrary, a super-linear growth (β>1) favors flux intensity and promotes concentrated transport, leading to the emergence of steady-state “singular” and “fractal-like” configurations that resemble those of Branched Transport Problems. We derive a numerical discretization of the proposed model that is accurate, efficient, and robust for a wide range of scenarios. For β>1 the numerical model is able to reproduce highly irregular and fractal-like formations without any a-priory structural assumption.
Branching structures emerging from a continuous optimal transport model
Facca E.;
2021
Abstract
Recently a Dynamic-Monge-Kantorovich formulation of the PDE-based [Formula presented]-optimal transport problem was presented. The model considers a diffusion equation enforcing the balance of the transported masses with a time-varying conductivity that evolves proportionally to the transported flux. In this paper we present an extension of this model that considers a time derivative of the conductivity that grows as a power-law of the transport flux with exponent β>0. A sub-linear growth (0<β<1) penalizes the flux intensity and promotes distributed transport, with equilibrium solutions that are reminiscent of Congested Transport Problems. On the contrary, a super-linear growth (β>1) favors flux intensity and promotes concentrated transport, leading to the emergence of steady-state “singular” and “fractal-like” configurations that resemble those of Branched Transport Problems. We derive a numerical discretization of the proposed model that is accurate, efficient, and robust for a wide range of scenarios. For β>1 the numerical model is able to reproduce highly irregular and fractal-like formations without any a-priory structural assumption.I documenti in SFERA sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
