The Bullwhip effect in water demand management: taming it through an artificial neural networks-based system

被引:3
|
作者
Ponte, Borja [1 ]
Ruano, Laura [1 ]
Pino, Raul [1 ]
de la Fuente, David [1 ]
机构
[1] Univ Oviedo, Polytech Sch Engn, Gijon 33204, Spain
关键词
artificial neural networks; Bullwhip effect; water demand management; FEEDBACK; MODELS;
D O I
10.2166/aqua.2015.087
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The Bullwhip effect (BE) refers to the amplification of the variance of orders and inventories along the supply chain as they move away from the customer. This is considered as the main cause of inefficiencies in the management of a traditional supply chain. However, the BE is not relevant in the classic system of water distribution, based on long-term supply management. Nevertheless, current circumstances have drawn a new context, which has introduced the concept of water demand management, in which efficiency and sustainability are of great importance. Then, the time horizon of management has decreased enormously and the supply time takes on an important role. Therefore, the BE must be considered, as it significantly raises the costs of management. On the one hand, this paper brings evidence that the BE appears in a system of real-time management of water demand. On the other hand, it proposes the application of artificial intelligence techniques for its reduction. More specifically, an advanced forecasting system based on artificial neural networks has been used. The BE is heavily damped.
引用
收藏
页码:290 / 301
页数:12
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