Forecasting Intermittent Demand with Generalized State-Space Model

Author(s):  
Kei Takahashi ◽  
Marina Fujita ◽  
Kishiko Maruyama ◽  
Toshiko Aizono ◽  
Koji Ara
Author(s):  
Andressa C. Schittler ◽  
Douglas Pappis ◽  
Cassiano Rech ◽  
Alexandre Campos ◽  
Marco A. Dalla Costa

Author(s):  
Dhruv Gupta ◽  
Christos T. Maravelias

We present a generalized state-space model formulation particularly motivated by an online scheduling perspective. Through these proposed generalizations, we enable a natural way to handle routinely encountered disturbances and a rich set of corresponding counter-decisions. Thereby, greatly simplifying and extending the possible application of mathematical programming based online scheduling solutions to diverse application settings.


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