A review on the electric vehicle routing problems: Variants and algorithms

Over the past decade,electric vehicles(EVs)have been considered in a growing number of models and methods for vehicle routing problems(VRPs).This study presents a comprehensive survey of EV routing problems and their many variants.We only consider the problems in which each vehicle may visit multiple vertices and be recharged during the trip.The related literature can be roughly divided into nine classes:Electric traveling salesman problem,green VRP,electric VRP,mixed electric VRP,electric location routing problem,hybrid electric VRP,electric dial-a-ride problem,electric two-echelon VRP,and electric pickup and delivery problem.For each of these nine classes,we focus on reviewing the settings of problem variants and the algorithms used to obtain their solutions.

Integrating BIM and machine learning to predict carbon emissions under foundation materialization stage:Case study of China’s 35 public buildings

For the significant energy consumption and environmental impact,it is crucial to identify the carbon emission characteristics of building foundations construction during the design phase.This study would like to establish a process-based carbon evaluating model,by adopting Building Information Modeling(BIM),and calculated the materialization-stage carbon emissions of building foundations without basement space in China,and identifying factors influencing the emissions through correlation analysis.These five factors include the building function type,building structure type,foundation area,foundation treatment method,and foundation depth.Additionally,this study develops several machine learning-based predictive models,including Decision Tree,Random Forest,XGBoost,and Neural Network.Among these models,XGBoost demonstrates a relatively higher degree of accuracy and minimal errors,can achieve the RMSE of 206.62 and R2 of 0.88 based on testing group feedback.The study reveals a substantial variability carbon emissions per building’s floor area of foundations,ranging from 100 to 2000 kgCO_(2)e/m^(2),demonstrating the potential for optimizing carbon emissions during the design phase of buildings.Besides,materials contribute significantly to total carbon emissions,accounting for 78%e97%,suggesting a significant opportunity for using BIM technology in the design phase to optimize carbon reduction efforts.