中文摘要：

以某纺织企业的产品运输流程和企业生产、销售对产品运输的具体需求为例，建立以总运输费用最低为目标函数，以每个生产地每种产品的生产量、每个销售地每种产品的销售量，以及每种产品的单位运价为约束条件的多种产品运输模型．设计具有全局优化、收敛速度快的遗传算法，并对该模型进行优化求解．通过与传统算法的比较，说明采用遗传算法求出的运输总费用优于用内点算法计算出的结果，即对于大规模的多产品运输问题，采用遗传算法优化性能更好，不易陷入局部最优，且其收敛速度也优于内点算法．

英文摘要：

Taking a textile enterprise product transportation process, and specific needs of product transportation about enterprise production and sales for example, builting transportation model of multiple products, in which the object function is to minimize the total transportation cost, and the constraint condition is the production of each product in each pro- ducer and the sales volume of product in each seller as well as the unit transportation rate of each product. Designing ge- netic algorithm with global optimization and the convergence speed, and use it to obtain the optimization solution of the model. Compared with the traditional algorithm, the result shows that the total transportation cost figured out by using the genetic algorithm is better than that by using interior point algorithm. That is, for large-scale multiple product trans- portation problems, the genetic algorithm has better optimization performance, and is not easy to fall into local optimum, and the convergence speed is also superior to the interior point algorithm.