Title
A Stochastic Model for Implementing Postponement Strategies in Distribution Networks
Abstract
An essential aspect of modern logistic concepts is the question how to deal with demand uncertainties. One concept that has been proposed but not yet fully explored in this context is postponement. In this concept the finalization of a product is procrastinated, i.e., the final products are not completed in single factories but in facilities in a distribution network that are located on the itinerary from factories to customers. Up to now, mainly global evaluations of pros and cons of postponement strategies are available. In order to allow for decision making for specific postponement implementations including its various effects in distribution networks, a double-stage stochastic mixed inte-ger linear programming (MIP) model is presented in this paper. This model supports managers to find out appropriate implementations of postponement strategies to manage demand uncertainties. By solving a set of problem instances it becomes obvious that the presented model formulation can be used to obtain solutions with (commercially) available mathematical programming software.
Year
DOI
Venue
2011
10.1109/HICSS.2011.31
System Sciences
Keywords
Field
DocType
decision making,integer programming,linear programming,logistics,production facilities,stochastic processes,uncertain systems,decision making,demand uncertainties,distribution networks,facilities,mathematical programming software,mixed integer linear programming,modern logistic concepts,postponement strategies,product finalization,stochastic model
Postponement,Mathematical optimization,Computer science,Operations research,Implementation,Software,Integer programming,Finalization,Supply chain,Stochastic modelling,Linear programming,Management science
Conference
ISSN
ISBN
Citations 
1530-1605
978-1-4244-9618-1
1
PageRank 
References 
Authors
0.36
15
4
Name
Order
Citations
PageRank
Stefan Guericke110.36
Achim Koberstein2809.48
Frank Schwartz3101.78
Stefan Voß459246.77