摘要
设计了一个启发式算法(SPM)来优化在线订单的接收及生产排序过程,以达到最大化长期单位时间订单收益的目标.所研究问题的背景是单阶段按订单生产(MTO)的制造系统,当顾客到来时,生产商经过决策并问询给顾客严格的交货期,顾客依据该交货期按照一定概率确认订单.SPM算法把新订单自身与当下临时加工序列一同包含在决策机制中,来衡量每一个到达的订单的潜在价值.通过数值仿真实验,在合理的参数设定下,SPM算法相对于FCFS的简单算法对于较为密集订单的处理具有更大的优势,对效益的提升十分显著.
In this study, a heuristic algorithm named SPM（Standard Profit Maximization） is designed to optimize the process of accepting and scheduling online orders to maximize the profit per unit time in the long run. The studied problem is set in a single-stage MTO（Make To Order） manufacturing system. When an order arrives, the manufacturer decides to quote an accurate due date to the customer, and the customer confirms the order according to some probability. The algorithm evaluates the potential value of an order by incorporating the order itself into the current temporary schedule. In the computational experiments, SPM significantly outperforms the naive algorithm based on FCFS（First Come First Serve） when the orders arrive at a moderately fast pace.
出处
《复旦学报（自然科学版）》
CAS
CSCD
北大核心
2014年第5期584-590,共7页
Journal of Fudan University：Natural Science
关键词
交货期问询
生产排序
订单不确定
收益管理
due-date quotation
scheduling
uncertain order
revenue management
