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Quantitative Inventory Modeling and Future Trends in Supply Chain Management

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Financial Engineering, E-commerce and Supply Chain

Part of the book series: Applied Optimization ((APOP,volume 70))

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Abstract

There is a trend in coordinating all the firm’s activities as an integrated system called supply chain. However, the treatment of inventories remains of high interest in all enterprises within this framework. Inventory is a major investment in most companies and it influences their flexibility and success. Traditionally, a large number of research activities have been focused on finding the best answer to the two basic questions concerning inventory management, i.e., when and how much to order. The majority of those research works have used quantitative methods to find the optimal solution. However, in recent years, because of innovations in technology, changes in customer expectations, and availability of new methods of production, attention has been attracted to a philosophy, also known as the JIT method, which considers inventory as a waste. The purpose of this paper is to present a paradigm of classical mathematical inventory models, to give a short review of their evolution into more realistic representations of the inventory system, and to discuss new trends in and the future of inventory management in the era of globalization and networking.

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Author information

Authors and Affiliations

  1. DSS Laboratory Department of Production and Industrial Engineering, Technical University of Crete, Greece

    Athanasia Karakitsiou & Athanasios Migdalas

Authors
  1. Athanasia Karakitsiou
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  2. Athanasios Migdalas
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Editors and Affiliations

  1. University of Florida, Gainesville, Florida, USA

    Panos M. Pardalos

  2. Deal-Fx, Athens, Greece

    Vassilis K. Tsitsiringos

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© 2002 Springer Science+Business Media Dordrecht

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Karakitsiou, A., Migdalas, A. (2002). Quantitative Inventory Modeling and Future Trends in Supply Chain Management. In: Pardalos, P.M., Tsitsiringos, V.K. (eds) Financial Engineering, E-commerce and Supply Chain. Applied Optimization, vol 70. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-5226-7_16

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  • DOI: https://doi.org/10.1007/978-1-4757-5226-7_16

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4419-5222-6

  • Online ISBN: 978-1-4757-5226-7

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