Carbon Emission-based Optimization And Algorithm For Urban Delivery Routes

Based on the current situation of the improvement of China’s national economy and the significant improvement of people’s living standards,the express delivery industry has ushered in a golden period of development.However,considering that the express delivery industry mostly relies on road transportation,the greenhouse effect and extreme weather conditions it brings have gradually attracted the attention of citizens and governments.Therefore,this article takes the low-carbon,green,energy-saving,and sustainable development concept as the guiding principle,rationally plans urban express delivery routes,effectively improves delivery efficiency,and achieves low-carbon express delivery.Based on existing research,this article first introduces the basic theory of urban express delivery route,including the specific classification of vehicle routing problem and its commonly used solution algorithms.Regarding the express delivery service process,this article presents its carbon emission influencing factors and carbon emission calculation models,effectively demonstrating the impact of vehicle speed and load on carbon emissions during urban express delivery.On this basis,taking urban express delivery as the research object,considering the constraints of vehicle load,delivery time window,and delivery time connection,a city express delivery path optimization model is constructed,which coordinates the fixed use cost of vehicles,driver cost,transportation cost,and carbon emission cost to achieve the optimal solution.To solve the model,a genetic algorithm is designed with encoding,selection,and crossover as its core components.Considering the limitations of algorithms easily falling into local optima,this article improves the selection operator by designing a local search strategy based on the genetic algorithm framework and incorporating a large neighborhood search algorithm.Additionally,an elite preservation strategy is implemented to enhance the convergence and accuracy of the algorithm.Finally,using delivery data from a certain express delivery company as the research object,Python web scraping software is used to analyze and process road network data.Based on this,the model and algorithm are implemented through programming in Matlab.The delivery routes of various express vehicles during working hours are adjusted and optimized,resulting in a runtime of 564 seconds and 300 iterations,which validates the effectiveness of the model and algorithm.The analysis of the results leads to the following conclusions:(1)Effectively reducing comprehensive operating costs.By optimizing the existing express delivery plans while meeting the constraints of urban residents’ express demand,the comprehensive operating costs of express delivery are effectively reduced.For example,by reducing two delivery vehicles,the fixed operating costs of vehicles decrease from 979.32 yuan to 771.89 yuan,a decrease of 21.18%.The carbon emissions are reduced from 59.7 kilograms to 48.429 kilograms,a decrease of 18.87%.The transportation distance decreases from 142.9kilometers to 96.5 kilometers,a decrease of 32.47%.(2)exactly attainment of optimal solutions.Analyzing and comparing the results of solving six examples using traditional genetic algorithms,large neighborhood search algorithms,and the improved genetic algorithm designed in this article,it is not difficult to observe that the improved genetic algorithm converges faster and frequently surpasses local optima,gradually approaching the global optimal solution.When the departure time is 9:00,the improved genetic algorithm yields delivery costs and carbon emissions that are 7.12% and9.3% lower,respectively,than the traditional genetic algorithm.Furthermore,compared to the results obtained by the large neighborhood search algorithm,the improved genetic algorithm reduces transportation costs by approximately 3.8% and carbon emissions by approximately8.1%.(3)Optimizing the departure times of vehicles can effectively reduce delivery costs and carbon emissions.Analyzing the impact of vehicle departure times on delivery costs and carbon emissions,when the vehicle departs at 9:10,the comprehensive delivery cost and carbon emissions reach their lowest levels,amounting to 696.24 yuan and 41.79 kilograms,respectively.When the vehicle departs at 8:00,the comprehensive delivery cost and carbon emissions reach their highest levels,amounting to 771.89 yuan and 48.429 kilograms,respectively.The comprehensive delivery cost and carbon emissions decrease by 9.8% and13.7%,respectively.This demonstrates that reasonable vehicle departure times and routing can effectively achieve low-carbon express delivery in urban areas.