遗传算法求解多工厂供应链排序问题

Genetic algorithms for multi-plant supply chain scheduling problem

在供应链管理问题中,供应链排序问题一直是重点研究对象,文中针对定制产品在生产过程中随机性和模糊性并存的情况,研究了一类多工厂供应链排序问题。在该问题中,以完成所有订单的最长提前期和生产运输总成本为评价指标,建立问题的模糊随机期望值模型,采用遗传算法求解问题,并通过仿真实验验证了模型及算法的有效性。

Supply chain scheduling problem has always been a focus of research in supply chain management. The multi-plant supply chain scheduling problem with random and fuzzy in the process of production of customized products was studied on. This paper establishes a fuzzy stochastic expected value model in this problem for considering the longest lead time of completing all orders and the total cost of producing and transiting all orders as evaluation index. It solves the problem by using genetic algorithm and then verifies the effectiveness of the model and algorithm through the simulation results.