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Introduction

Chapter
Part of the Lecture Notes in Economics and Mathematical Systems book series (LNE, volume 636)

Abstract

Striving for operational and strategic excellence, companies have continuously been trying to improve their business processes in the past years. As sophisticated planning processes are often seen as a key enabler for efficient business processes, this has led to an increased focus on developing methods to optimize processes using mathematical methods in cases where decision problems are too complex to be solved by a human decision maker. In order to transfer such methods into practice, IT-based systems such as Advanced Planning Systems (APS) that make use of these optimization methods to support and automate planning processes and execute the resulting plans are essential.

In companies handling physical goods, the planning processes for production and logistics often involve a high amount of complexity. This complexity results on the one hand from the fact that companies frequently have multiple locations in various countries and offer a large product variety associated with high manufacturing complexity. On the other hand, companies are increasingly embedded in complex global supply networks with a large number of actual or potential suppliers and customers. From the viewpoint of an individual company, its suppliers and customers and the actors further upstream or downstream are referred to by the term Supply Chain (SC). Thus, each company may be part of multiple “subjective” supply chains of other companies (Bretzke, 2006).

Keywords

Product Substitution Transshipment Problem Human Decision Maker Inventory Control Model Advance Planning System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. Begnaud, J., Miller, L., & Benjaafar, S. (2006). The multilevel lot sizing problem with flexible production sequences (Working paper). Minnesota: Industrial and Systems Engineering Department of Mechanical Engineering, University of Minnesota, MN.Google Scholar
  2. Bretzke, W. (2006). SCM: Sieben Thesen zur zukünftigen Entwicklung logistischer Netzwerke. Supply Chain Management, 6, 7–15.Google Scholar
  3. Hale, W., Pyke, D. F. P., & Rudi, N. (2000). An assemble-to-order system with component substitution (Working paper). Hanover, NH / Rochester, NY: Amos Tuck School, Dartmouth College / The Simon School, University of Rochester.Google Scholar
  4. Naim, M., Potter, A., Mason, R., & Bateman, N. (2006). The role of transport flexibility in logistics provision. The International Journal of Logistics Management, 17(3), 297–311.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  1. 1.Department of Law, Business and Economics Chair of Operations ResearchTechnische Universität DarmstadtDarmstadtGermany

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