摘要
为了研究随机需求下供应链系统中多零售商的横向转载问题,提出了一种基于随机规划方法的多零售商横向转载模型,并设计了一种启发式算法用于模型求解.考察由一个外部供应商和多个零售商组成的供应链系统,供应商和零售商均采用order-up-to方法控制库存,零售商面临随机性需求且相互之间存在横向转载.在横向转载经典假设条件下,构建了以供应链总成本为目标的混合0-1规划模型.考虑到该模型中存在随机变量,将模型转化为随机期望值规划模型进行求解,结合随机拟梯度算法及遗传算法设计了一类启发式算法来求解模型,给出了详细的求解过程.利用数值算例的仿真结果验证了模型及算法的有效性,还就需求相关程度的影响及转载假设条件的影响进行了详细分析.研究结果表明:模型及算法对存在横向转载的供应链系统确定最优库存水平是相当有效的.
In order to derive optimal lateral transshipment policy among retailers in supply chain system under stochastic demand environment,this paper developed a stochastic programming method to model the multilocation lateral transshipment problem in supply chain system.We considered a supply chain system that includes a supplier and multi retailers;they all adopt order-up-to approach to control inventories. Retailers faced stochastic demand and shared their inventories among each other—a retailer would transship residual stocks to other retailers which faced residual demand after demand realized.Based on the traditional hypothetical conditions,we developed a mix 0-1 programming model under system total cost minimization objective.Because of the stochastic vectors in the model,we covert the model to a stochastic expected value programming model,designed a heuristic algorithm that combined stochastic quasi gradient algorithm（SQGA） with genetic algorithm（GA）,and explained the solution procedure. Numerical examples showed the efficiency of the model and algorithm.Besides,we investigated the case of coefficient demand and the case of violation of traditional transshipment conditions.Numerical results show that this model and algorithm is considerably effective in determining the optimal order-up-to points in supply chain system with retailers＇ lateral transshipment existence.
出处
《系统工程理论与实践》
EI
CSSCI
CSCD
北大核心
2012年第4期738-745,共8页
Systems Engineering-Theory & Practice
基金
国家自然科学基金(70761001)
国家社会科学基金(10CGL025)
教育部规划基金(10YJA630147):江苏省高校哲学社会科学基金(2010SJB630055)
江苏省高校青蓝工程优秀青年骨干教师基金(苏教师2010第27号)
南通大学人才引进基金(08R05)
南通大学人文社会科学基金(09W021)
关键词
供应链
横向转载
随机规划
随机拟梯度算法
遗传算法
supply chain
lateral transshipment
stochastic programming
stochastic quasi gradient algorithm
genetic algorithm
