基于Newsvendor型产品特性的FJSP问题研究

针对新时代环境下Newsvendor型产品销售期短、期末未出售产品价值递减的产品特点,生产链要求位于上游的供应商必须快速加工出所需的工件,否则将面临着线性递增的拖期惩罚。在面对基于Newsvendor型产品的柔性作业车间调度问题时,设计了一种加入禁忌搜索的混合遗传算法,扩大了解的搜索范围,避免了传统遗传算法容易陷于局部最优的缺陷。最后利用混合遗传算法对一个仿真案例进行求解。

Research of the FJSP based on the Newsvendor-type products

In modern times, Newsvendor-type products sale in a short period and the value of the products are diminishing. So the supplier on the upstream of the production chain should make products and send them to the producer as soon as possible, or the supplier would be suffered a increased punishment for its delay. In order to solve the flexible job-shop scheduling problem of Newsvendor-type products, a method of combined Genetic Algorithm with Tabu Search be designed. The algorithm is used to expand the search range of solutions and avoid the defects of easily into local optimal of the traditional genetic algorithm. At the end of thesis, the method is used to solve a simulation case.