Solving stochastic programming models in supply chain design using sampling heuristics

被引：4
|
作者：
Mo, Yin [1 ]
Harrison, Terry P. [1 ]
Barton, Russell R. [1 ]
机构：
[1] Penn State Univ, Dept Supply Chain & Informat Syst, University Pk, PA 16802 USA
来源：
IMA JOURNAL OF MANAGEMENT MATHEMATICS | 2011年 / 22卷 / 01期
关键词：
stochastic programming; supply chain design; uniform experiment designs; FACILITY LOCATION;
D O I：
10.1093/imaman/dpq003
中图分类号：
C93 [管理学];
学科分类号：
12 ; 1201 ; 1202 ; 120202 ;
摘要：
We consider a supply chain design problem to provide new ways to buffer the effect of demand uncertainty when designing supply chains. The problem is formulated as a two-stage stochastic programming with fixed recourse. A special sampling procedure based on uniform experiment designs provides superior quality approximate solutions for a simple supply chain structure when demands are correlated.
引用
收藏
页码：65 / 77
页数：13
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