Budget-constrained rail electrification modeling using symmetric traffic assignment -- a North American case study

TL;DR

This paper models budget-constrained rail electrification on North American networks considering user equilibrium freight flows, nonseparable link performance, and uses a genetic algorithm to analyze impacts of demand and operational costs.

Contribution

It introduces a bi-level model with symmetric Jacobian link functions for rail electrification, solved via genetic algorithms with domain-specific optimizations.

Findings

Broad connectivity enhances electrification benefits.

Higher demand favors east and gulf coast corridors.

Higher operational costs favor mountainous route electrification.

Abstract

We consider a budget constrained rail network electrification problem with associated changes in costs of energy usage (via path gradient and curvature), operations, and long-term maintenance. In particular, we consider that freight flows on such a network form a user equilibrium. Interactions between electric and diesel trains on the same corridor are represented with nonseparable link performance functions, which nevertheless have a symmetric Jacobian. This bi-level formulation is solved for the North American railroad network using a genetic algorithm (GA), incorporating domain-specific insights to reduce the number of solutions which must be considered. We analyze solution characteristics and decision-making implications. Results show that broad connectivity would be beneficial for most impact. Increasing demand shifts electrified corridors towards the more populous east and gulf coasts, while increased operational costs results in electrification of routes through mountainous terrains.