Optimization Of Vehicle Route In Cold-chain Logistics For Fresh Food

With the variety of diet structure nowadays, the need for fresh food has increased a lot. Fresh food is characteristic by its short shelf life, high rate of corruption and difficulty in keeping fresh, so it needs to be supported by Cold-chain Logistic for distribution. Unlike other advanced countries, the development of Cold-chain Logistic was late and laggard in China, thus there a series of problems such as the undeveloped Cold-chain preservation technology and lacking of professional working staffs, which causes the high cost and low quality of cold-chain distribution. As an essential part of Cold-chain Logistic, the optimization of the route of Cold-chain distribution has a direct influence on the total cost and quality of the Cold-chain distribution. The subject of this paper is to optimize the route of Cold-chain distribution for fresh food in order to reduce the total cost and improve the quality of fresh food in distribution, and to meet the various customers’ needs and ensure the safety in Cold-chain distribution.This paper begins with the analysis of the features of Cold-chain distribution for fresh food, such as short shelf life, high rate of corruption, and also listing a series of costs in Cold-chain distribution, like the fee for the use of the refrigerated vehicles, transportation cost and the cost of refrigerant consumed, est. Based on this analysis, the paper then build a basic model to optimize the route of Cold-chain distribution for fresh food, the objective function minimizes the sum of the above costs in Cold-chain distribution for fresh food. The model then is modified in consideration of the cost caused by the corruption of the fresh food during the distribution, different requirements of delivery time and avoiding fatigue driving. The author also designs a program with Genetic Algorithm to solve the mode. At the end of the paper, the author uses an example of an aquatic products enterprise to testify the rationality and feasibility of the model and program.