The Electric Location-Routing Problem: Improved Formulations and Effects of Nonlinear Charging

TL;DR

This paper advances Electric Location-Routing Problem models by incorporating nonlinear charging, multiple station types, and improved formulations, leading to more accurate and effective EV fleet and infrastructure planning.

Contribution

It introduces novel formulations for ELRP that account for nonlinear charging and multiple station types, significantly improving solution quality over existing models.

Findings

Reduced average solution gap from 29.1% to 11.9%.

Improved solutions for 28 out of 74 instances.

Provided insights into nonlinear charging effects on infrastructure planning.

Abstract

Electric Location-Routing models (ELRP) can contribute to the effective planning of electric vehicles (EVs) fleets and charging infrastructure within EV logistic networks because it simultaneously combines routing and location decisions to find optimal solutions to the network design. This study introduces ELRP models that incorporate nonlinear charging process, multiple charging station types and develop new improved formulations to the problem. Existing ELRP models commonly assume a linear charging process and employ a node-based formulation for tracking EV energy and time consumption. In contrast, we propose novel formulations offering alternative approaches for modeling EV energy, time consumption, and nonlinear charging. Through extensive computational experiments, our analysis demonstrates the effectiveness of the new formulations, reducing the average gap from 29.1% to 11.9%, yielding improved solutions for 28 out of 74 instances compared to the node-based formulation. Moreover, our findings provide valuable insights into the strategic implications of nonlinear charging in ELRP decision-making, offering new perspectives for planning charging infrastructure in EV logistic networks.