Double Carbon Targets Under Cold Chain Distribution Route Optimization

With the rapid development of science and technology,people more and more is also high to the requirement of material life,especially to the increasing demand in different parts of the fresh goods,which prompted the rapid development of cold chain logistics.Compared to common logistics,cold chain logistics has the characteristics of energy intensive and high carbon emissions,with the double carbon strategic background of green economy.Therefore,the enterprise should not only pay attention to the development of cold chain logistics distribution,also should pay attention to the development of low carbon environmental protection,shoulder the responsibility of the green logistics.Different transportation and delivery route,the vehicle’s range is different,the distance can also lead to different energy consumption and co2 emissions of the vehicle.Path optimization is one of the factors that affect carbon emissions,and easy to control one of the factors.Therefore,cold-chain logistics distribution path optimization research caused the enterprise,the wide attention of scholars.Because fresh goods are perishable,the timeliness of cold chain logistics distribution has strict requirements.To improve customer satisfaction,it is necessary to enhance the transport and distribution service of cold chain logistics.Therefore,this paper mainly designed the distribution path of cold chain logistics with the goal of maximizing customer satisfaction,minimizing total cost and maximizing carbon emission benefit.Among them,the total cost includes not only the fixed cost,transportation cost,refrigeration cost and contract cost,but also the carbon emission cost which is not easy to be calculated.Through carbon tax,the carbon emission cost is transformed into the cost which is easy to be quantified.This article based on chaos genetic algorithm for the design of double cold-chain logistics distribution route optimization are applied to solve the multi-objective problem,genetic algorithm has the principle to understand,control parameters,the search process is simple,less search has the advantages of potential parallelism,but at the same time it still has the defects of easy to fall into local optimum.To the disadvantages of the genetic algorithm,this paper introduced the chaos genetic algorithm in order to improve its own deficiencies,and using multi-objective path optimization simulation of cold chain logistics,contrast analysis,the result of the chaos genetic algorithm,genetic algorithm(ga)to prove the feasibility and the superiority about the chaos genetic algorithm.Next to the example simulation,the simulation results show that chaos genetic algorithm makes the distribution route distance shortened,but the convergence speed raised,verify the effectiveness of the chaos genetic algorithm to solve practical problems.Finally based on A empirical research of the cold chain transportation distribution problem of the state-owned enterprises,the results show that the chaos genetic algorithm on the cold chain logistics cost and carbon emissions costs less than genetic algorithm(ga),carbon emissions benefits the same as the genetic algorithm(ga),customer satisfaction is A bit smaller than genetic algorithm(ga),and according to the simulation results for A enterprise put forward the corresponding optimization strategy,for A transportation and delivery of enterprise management,customer management,provide some references for carbon management advice.