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Using stochastic programming on ATP/CTP under uncertain ATO environment
Sun DC(孙德厂); Shi HB(史海波); Han ZH(韩忠华); Liu C(刘昶)
作者部门数字工厂研究室
关键词Adenosinetriphosphate Automobile Manufacture Genetic Algorithms Monte Carlo Methods Production Engineering Sales Stochastic Programming Uncertainty Analysis
发表期刊International Journal of Modelling, Identification and Control
ISSN1746-6172
2013
卷号20期号:3页码:242-252
收录类别EI
EI收录号20134316902014
产权排序1
摘要For the companies adopting assemble-to-order (ATO) production strategy, providing accurate and reliable order promising is an important issue especially subject to the uncertainty. The ATO production system has the following characteristics. There are no finished goods in the strict sense. Inventory is holding at component level. The material and capacity planning is driven by the sales forecasting. Assembly scheduling is driven by the customer orders. We reviewed the existing order-promising researches which are mostly determined by the environment. In the base of analysis the influence mechanism of uncertainty and available-to-promise/capable-to-promise (ATP/CTP) allocation approach, we establish a stochastic dependent-chance programming model considering the available resources which are fluctuant. The objective is to maximise the chance of acceptance of the orders as much as possible. This means higher utilisation of assembly capacity. The available amount of resources obeyed some kind of common distribution. We develop a hybrid genetic algorithm (HGA) for solving the stochastic programming model; the main steps are chance function construction, Monte Carlo simulation, neural network approach and genetic algorithm (GA). We implement the model and algorithm in an automobile manufacturer, the uncertainty variables are fitted using historical data. The experiment result verified that the model and solver are valid. Copyright © 2013 Inderscience Enterprises Ltd.
语种英语
文献类型期刊论文
条目标识符http://ir.sia.cn/handle/173321/13946
专题数字工厂研究室
通讯作者Sun DC(孙德厂)
作者单位1.Shenyang Institute of Automation, Chinese Academy of Science, No. 114 Nanta Street, Shenyang 110016, China
2.University of the Chinese Academy of Science, No. 19A Yuquan Road, Beijing 100049, China
推荐引用方式
GB/T 7714
Sun DC,Shi HB,Han ZH,et al. Using stochastic programming on ATP/CTP under uncertain ATO environment[J]. International Journal of Modelling, Identification and Control,2013,20(3):242-252.
APA Sun DC,Shi HB,Han ZH,&Liu C.(2013).Using stochastic programming on ATP/CTP under uncertain ATO environment.International Journal of Modelling, Identification and Control,20(3),242-252.
MLA Sun DC,et al."Using stochastic programming on ATP/CTP under uncertain ATO environment".International Journal of Modelling, Identification and Control 20.3(2013):242-252.
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