Controlling inventory on electric roads

TL;DR

This paper introduces the Electric Roads Routing Problem, a novel model for optimizing routing and inventory control of hybrid vehicles on electric road networks considering variable costs, demand uncertainty, and vehicle load.

Contribution

It formulates a new stochastic optimization problem for electric road systems and proposes a mathematical programming heuristic to solve it effectively.

Findings

The heuristic performs well on realistic instances.

Different routing strategies emerge based on fuel and electricity costs.

Electric road systems can significantly influence delivery efficiency.

Abstract

Electric road systems (ERS) are roads that allow compatible vehicles to be powered by grid electricity while in transit, reducing the need for stopping to recharge electric batteries. We investigate how this technology can affect routing and delivery decisions for hybrid heavy good vehicles (HGVs) travelling on a ERS network to support the demand of a single product faced by a set of retailers in the network. We introduce the Electric Roads Routing Problem, which accounts for the costs of electricity and fuel on a ERS network, consumption that are affected by the battery level of the vehicle in each step of the journey, the routing decisions and the variable weight of the vehicle, which depends on vehicle load and delivery decisions. In particular, we study a stochastic demand version of the problem, formulating a mathematical programming heuristic and proving its effectiveness. We use our model on a realistic instance of the problem, showcasing the different strategies that a vehicle may follow depending on fuel costs in relation to the costs of electricity.