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

页码：65 / 77

页数：13

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