首页|Automated,economical,and environmentally-friendly asphalt mix design based on machine learning and multi-objective grey wolf optimization
Automated,economical,and environmentally-friendly asphalt mix design based on machine learning and multi-objective grey wolf optimization
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The increasing impact of the greenhouse effect on ecosystems is prompting transportation agencies to seek methods for reducing CO2 emissions during pavement construction and maintenance.Additionally,the laboratory mix design process,which involves selecting aggregate gradation and binder content,is time-consuming and labor-intensive.To accelerate the traditional mix design procedure,this study presented a mix design pro-cedure that can automatically determine gradation and binder content based on machine learning(ML)and a meta-heuristic algorithm.Specifically,ML approaches were employed to model the relationship between volumetric properties(mixture bulk specific gravity(Gmb)and air void(VV))and both mixture component properties and mixture proportion,based on a dataset collected from literature with 660 mixture designs.Integrated with the prediction of ML models and the modified multi-objective grey wolf optimization(MOGWO)algorithm,an automatic asphalt mix design was proposed to pursue three goals,including W,cost,and CO2 emission.The results indicated that least squares support vector regression(LSSVR)and eXtreme gradient boosting(XGBoost)achieved the highest predic-tion accuracies(correlation coefficient:0.92 for W and 0.96 for Gmb).The MOGWO algo-rithm successfully found the 26 optimal mix designs for the case of W vs.cost vs.CO2 emission.Compared to the traditional laboratory design,the optimal mixture with VV of 4％achieves a cost saving of 2.46％and a reduction of 4.03％in carbon emission.The volumetric properties of the mixtures output by the approach also align closely with values measured in a laboratory.
Department of Civil and Environmental Engineering,Virginia Polytechnic Institute and State University,Blacksburg,VA 24061,USA
School of Environmental,Civil,Agricultural and Mechanical Engineering,University of Georgia,Athens,GA 30602,USA
Illinois Center for Transportation,Department of Civil and Environmental Engineering,University of Illinois Urbana-Champaign,Urbana,IL 61801,USA
Center for Integrated Asset Management for Multimodal Transportation Infrastructure Systems(CIAMTIS)US Department of Transportation,University Transportation Center,United States
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