满足服务时间条件下产品回收逆向物流网络模型

Reverse Logistics Network Model of Product Returns Under Service Time

面对日益增长的回收产品,回收产品的复杂性和不确定性令分销商或制造商头痛不已。本文提出一个非线性混合整数规划模型,利用遗传算法对模型求解,确定回收点和回收中心的数目及回收点作业的天数,在满足服务时间的条件下降低逆向物流成本,优化产品回收物流网络。

Facing the growing product returns, the distributors or the manufacturers really have a headache about the complexity and uncertainty of the product returns. This paper proposes a nonlinear mixed-integer programming model. To determine the number of collection points and collection center and days of collection points, a genetic algorithm is presented to solve it. Then we minimize the return cost and rationalize the network structure of product recovery under service time.