Optimization Of Low-carbon Cold Chain Distribution Route For Fresh Agricultural Products Based On Mixed Ant Colony Algorithm

With the enhancement of people’s lifestyles and the widening of distribution plateaus,the demand for fresh agricultural products has been continuously increasing.The cold chain dispatch of agricultural products is faced with great challenges.The increase in requirements for cold chain logistics of fresh agricultural products will cause an increase in the relevant values such as the transport turnover,logistics and vehicle distribution,carbon emissions,etc.,which will lead to an increase in all costs such as stationary costs,transport costs,freezing costs,carbon emission costs,fresh fruit loss costs and cost of penalties.Of these,the increase in carbon discharge may aggravate environmental pollution and impose a burden on the ecological environment,which is inconsistent with the low-carbon concept and the needs of a low-carbon economy that the country advocates.Therefore,we investigate the vehicle transportation path of fresh product cold chain logistics with the vehicle capacity and distribution time limitation to achieve the targets of reducing the total production cost,improving customer satisfactory and reducing carbon pollution.In this thesis,we firstly analyse the current study situation of low-carbon cold chain logistics for fresh farm products at home and a brief description of the theories related to low-carbon refrigeration logistics and route design and optimisation of distribution vehicles is given.Secondly,combining the characteristics of fresh agricultural products and their distribution requirements,a vehicle distribution path optimisation model for fresh agricultural products cold chain distribution is established based on the minimisation of total distribution cost as the objective function,taking into accounts carbon emissions.Then,a Hybrid Ant Colony algorithm is proposed to solve this optimal model.In the initial stage,the Initial Pheromone Distribution is produced by the Ant Colony Optimisation algorithm,while the crossover and transformation operations of the Genetic Algorithm are introduced,to overcome the drawback that the Ant Colonies algorithm is easy to fall into local optimum.Finally,to verify the efficacy of the hybrid ant colony algorithm,the experimental results were solved using Jiangxi J Cold Chain Logistics Co Ltd as an Example and by using MATLAB simulation software to derive the optimal distribution scheme and compare it with the original path obtained by the traditional ant colony algorithm.The result of the experiment shows that the mixed ant colony algorithm proposed in this thesis has the following advantages as compared with the traditional ant colony algorithm.Firstly,the rapid convergence enhances the speed of model solving.Second,the total cost and amount of carbon emissions required to arrive at the optimal distribution solution are reduced.Third,vehicle transport efficiency and customer satisfaction are boosted.The research in this thesis enriches the research content and scope of the Vehicle Path Optimisation problem,and provide a certain reference basis for companies to achieve low-carbon,low-cost optimal path delivery in the process of cold Chain distribution of fresh agricultural products.