Modular neural networks for recursive collaborative forecasting in the service chain

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In order to honour customer demand and sustain quality of service in BT’s service chain, accurate forecasting for customer demand is critical for optimal resource planning. In the more general context of service organisations, failure to allocate sufficient resources to meet anticipated customer demand will lead to delayed or disrupted service provision which in turn will result in degraded quality of service for customers and ill-balanced utilisation of available resources.In this paper, we present our ongoing research on a prototype collaborative forecasting application, whereas organisations involved in a supply and demand partnership aim to co-operate by sharing and jointly forming forecasts to aid in resource planning. We identify key theoretical and implementation specific issues related to the area of collaborative forecasting and discuss our initial modular artificial neural network approach to the problem.

论文关键词:Service chain,Collaborative forecasting,Neural networks

论文评审过程:Received 31 January 2007, Accepted 4 March 2008, Available online 31 March 2008.

论文官网地址:https://doi.org/10.1016/j.knosys.2008.03.021