New Models for Sustainable Logistics
Digiesi, Salvatore, Mascolo, Giuseppe, Mossa, Giorgio, Mummolo, Giovanni
Produktnummer:
18523042afe8d6436b804a4cec05ccd0da
Autor: | Digiesi, Salvatore Mascolo, Giuseppe Mossa, Giorgio Mummolo, Giovanni |
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Themengebiete: | Freight Transport Inventory Models SOQ Model Stochastic Variability Sustainable Logistics Sustainable Order Quantity |
Veröffentlichungsdatum: | 14.08.2015 |
EAN: | 9783319197098 |
Sprache: | Englisch |
Seitenzahl: | 98 |
Produktart: | Kartoniert / Broschiert |
Verlag: | Springer International Publishing |
Untertitel: | Internalization of External Costs in Inventory Management |
Produktinformationen "New Models for Sustainable Logistics"
This book introduces new inventory models to support decision-making when cost of externalities are jointly considered along with costs of logistics. Internalization of cost of externalities gives rise to new logistics costs estimates and functions which managers, researchers, lecturers and students should refer in facing with logistics issues. This book focuses on freight transports of industrial production systems. Logistics play a key role for industries since it reveals a critical function designed and managed to pursue economic goals. A large amount of literature is available providing models, which can be used to minimize logistic costs. However, these models usually neglect externalities.New Models for Sustainable Logistics: Internalization of External Costs in Inventory Management is comprised of three chapters. Chapter 1 provides a taxonomy of external costs figures as well as data set enabling the reader to perform reliable estimates of freight transport external costs. To this purpose, a full scale case study is developed. Chapter 2 describes a new sustainable inventory management model whose cost functions include externalities. The classical ‘Economic Order Quantity’ model is re-formulated and the new concept of Sustainable Order Quantity (SOQ) is defined. Finally, in Chapter 3 the SOQ model is formulated for different inventory management applications referred to both deterministic and stochastic production environments. Numerical examples are also provided.

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