Intermittent Demand Forecasting – Context, methods and applications

<p><i>Intermittent Demand Forecasting – Context, methods and applications</i> covers the entire breadth of work in intermittent demand forecasting and the very latest research findings in the following topics:<br /><br /></p> <ul> <li>time series (parametric) methods</li> <li>bootstrapping, both parametric and non-parametric</li> <li>causal models</li> <li>neural networks</li> </ul> <p>In order to enable a full understanding of how these methods may be implemented and how they may complement existing operational functions, other chapters include:<br /><br /></p> <ul> <li>demand classification (what exactly constitutes intermittence and how it may be distinguished from other patterns in operational terms)</li> <li>measures for assessing intermittent demand forecasting accuracy</li> <li>interactions between forecasting and stock control</li> <li>qualitative considerations (soft managerial issues that should be taken into account)</li> </ul> <p><br />The methods and approaches used in forecasting intermittent demands is relevant to many industries such as the military, aerospace, automotive, and information technology.</p>