Work

An effective and efficient matheuristic for the electric vehicle routing problem with capacitated recharging stations

Year: 2025

Type: article

Abstract: In this paper, we address the problem of routing a fleet of electric vehicles (EVs) to serve a set of customers, geographically distributed, within their time windows. We assume that EVs may also be recharged en route, and the amount of energy recharged at a recharging station (RS) is a decision variable itself, that is, partial recharges are allowed. We also assume that each RS has a limited number of chargers, and, therefore, possible overlaps at RSs among EVs have to be properly managed. We formulate the resulting electric vehicle routing problem with time windows and capacitated recharging stations (EVRPTW‐CRS) through mixed integer linear programming (MILP). Given the hardness of the EVRPTW‐CRS, we design a MILP‐based adaptive large neighborhood search. A result comparison with the state‐of‐the‐art exact algorithm shows both the effectiveness and the efficiency of the proposed matheuristic, on a set of benchmark instances, considering both a linear and a piecewise‐linear recharging function. An extensive sensitivity analysis on possible variation of some critical parameters is also carried out.

Source: International Transactions in Operational Research

DOI: 10.1111/itor.70104

Authors: Maurizio Bruglieri, Daniele Ferone, Paola Festa, Ornella Pisacane

Institutions: Politecnico di Milano, University of Naples Federico II, Marche Polytechnic University

Language: English

Topic: Vehicle Routing Optimization Methods

Subfield: Industrial and Manufacturing Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Sustainable cities and communities

Open Access status: hybrid

Estimated APC paid: $4,030