Research On Cold Chain Logistics Node Location Based On Genetic Algoritms

No matter in the developed and developing countries, frozen food has become the necessity of millions of households, Frozen food manufacturing has become one of the fastest-growing industries in the world. With the same time, the cold chain logistics the new supply chain system is gradually flourished. Nowadays, most developed countries such as Europe and the United States have established complete cold chain logistics system to make food fresh during transportation, which makes the loss rate droped to minimum. However, in our country the cold chain system is incomplete, the infrastructure and transport facilities are extremely backward. More than 80% fresh food transport by the normal way at room temperature, resulting in huge losses. That establish and improve the cold chain system has be imperative. During the construction of the cold chain logistics system, reasonable location of network nodes can save money speed up the flow of goods and increase companies'revenue. Therefore, the key of entire cold chain logistics system optimization is the location of network node.With regard to the study on cold chain logistics in China is still very less, and the existing research rarely consider the relationship among food corruption, time and temperature. According to a decade research by Arsdel, the relationship among rate of food corruption, time and temperature was a certain function, and that is the problem the well-known theory T.T.T. described. In this paper, based on T.T.T. theory and Arrhenius equation, the author deduced a function to describe the relationship among the rate of food corruption, time and temperature. Compared to general supply chain logistics, Cold chain logistics has special features, for example the product value gradually run off over time and can not recover again, penalty cost plays important role in total logistics cost. Therefore, taking the penalty function into account, the article used the deduced function to establish the penalty function and node location model. In view of NP-Hard nature of the model, the article used genetic algorithms to solve the model. In the solution process the software Matlab7.0 is need to program. Finally, this paper gave a case of A chilled company to analyze, to help this company choose the right place as cold chain distribution centers. By drawing the changes of the average of each generation's objective function value in the process of operations, the paper proved that the genetic algorithm can find near-optimal solution, and save a lot of logistics costs for the company. By comparing the different location results of considering the rate of deterioration or not, it can indicate that the rate of deterioration is able to effect the node location of cold chain logistics.