Litcius/Paper detail

Application of a Genetic Algorithm With a Fuzzy Objective Function for Optimized Siting of Electric Vehicle Charging Devices in Urban Road Networks

Aleksander Król, Grzegorz Sierpiński

2021IEEE Transactions on Intelligent Transportation Systems35 citationsDOI

Abstract

Minimization of negative environmental impact of transport cannot be pursued through mobility limiting, but rather through efficient utilization of natural resources. Some of the ways to reduce harmful pollution and noise include increasing the use of electric energy for transportation and developing electromobility. However, municipalities face difficult decisions connected with the siting of charging stations, for example, budget limitations are an important factor. The presented method allows for selecting a subset of existing parking lots where the charging devices will be sited. As the inputs, only easily accessible data is required. Applying a genetic algorithm combined with fuzzy logic and the Pareto front analysis, one could establish a set of optimal solutions for multiple pre-defined restrictive and partially contradictory criteria. The method has been discussed using a real example of a medium-sized city in southern Poland. Its results have also made it possible to verify whether a budget required for the planned investment is substantiated.

Topics & Concepts

Genetic algorithmFuzzy logicMinificationComputer scienceLimitingFunction (biology)Mathematical optimizationPareto principleTransport engineeringEngineeringMathematicsMachine learningArtificial intelligenceMechanical engineeringBiologyEvolutionary biologyElectric Vehicles and InfrastructureVehicle emissions and performanceTransportation and Mobility Innovations