| More and more companies have already considered the cost of logistics and distri bution as one of the important indicators affecting the development of enterprises.In particular,cold chain logistics has gained rapid development and attention in recent ye ars because of the distribution time and distribution efficiency of such products.The r equirements of the distribution environment are very strict.Whether or not the goods can be delivered in a standard and reasonable environment and whether the delivery v ehicles can deliver the goods within the time specified by the customers have a great i nfluence on the frozen and refrigerated products and food safety.Therefore,this paper reduces the cost of the delivery party by optimizing the distribution path of the cold c hain logistics.By establishing an integrated optimization platform,the delivered good s can be delivered to the customers faster and more rationally.This has great impact o n how to reduce business costs.Therefore,starting from the objective function of minimizing distribution costs,this p aper comprehensively considers the specific characteristics of cold-chain logistics,giv es relevant constraints,uses an improved genetic algorithm to iterate the given solutio n,and sends the improved new solution to The simulation software runs in simulation,and then the results obtained from the operation are sent to the genetic algorithm agai n for the next iteration,which is repeated in turn until the pre-given conditions are rea ched.Therefore,this article focuses on the following:(1)First,the relevant literature on cold chain and logistics distribution was studied,an d some existing problems and development status of cold chain logistics and distributi on were summarized.(2)For the VRP problem,this paper adopts the single-objective VRP model,that is,ta king the distribution cost as the minimum objective function,combining the characteri stics of the cold chain to give the relevant constraints,and building an optimizer throu gh the improved genetic algorithm in matlab.For the model,iterative optimization of each solution leads to a new set of solutions.(3)Considering that the VRP problem is a dynamic system of stochastic events,this a rticle uses the delivery time of the delivery vehicle and the loading and unloading spe ed of the delivery vehicle as two random variables.These two variables are set and est ablished in flexsim.A distribution system model,in the end,the data obtained from si mulation can be transmitted and saved in excel form in real time.(4)Finally,the optimizer model and the distribution system model are combined to create an integrated optimization platform to solve the model.Finally,an example is ver ified and analyzed.It can be clearly seen that the use of this method can greatly reduc e the optimization iteration.Number of times to get a more reasonable and satisfactor y solution.The innovation of this paper is that the research on VRP problem is not simply relying on the ordinary genetic algorithm to achieve,but through its own improved genetic al gorithm,a certain improvement has been made in the encoding method and the operat ion of selection,crossover,mutation,etc.The use of the improved genetic algorithm c an greatly reduce the number of iterations of the solution,and then use the integrated optimization platform to import the solution into flexsim for simulation.The new solu tion obtained from each simulation will be transferred to the matlab for the next time t hrough the excel form.The optimization iterations continue to repeat the above steps until they meet the pre-set conditions and terminate,so as to obtain a more realistic an d satisfactory solution. |
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