Method for stabilized tuning of demand models
First Claim
1. A computer-implemented method for tuning a demand model to a sales history that is stable with respect to random fluctuations in said sales history, said method comprising the steps of:
- providing a data storage having sales history data;
selecting a demand model, said demand model depending on a plurality of parameters including at least one demand parameter;
selecting a market model to describe how a subset of said at least one demand parameter is expected to vary according to external market information, said market model depending on at least one market parameter, which is external to said sales history data;
constructing a an effective figure-of merit function from said demand model and said market model, said effective figure-of-merit function having a plurality of parameters including said at least one demand parameter and said at least one market parameter; and
minimizing said effective figure-of-merit function with respect to said at least one demand parameter and said at lest one market parameter, thereby attaining an optimal value for said at least one demand parameter that is stable with respect to random fluctuations in said sales history data.
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Abstract
A method for tuning a demand model in manner that is stable with respect to fluctuations in the sales history used for the tuning is provided. A market model is selected, which predicts how a subset of the parameters in the demand model depends upon information external to the sales history; this model may itself have a number of parameters. An effective figure-of-merit function is defined, consisting of a standard figure-of-merit function based upon the demand model and the sales history, plus a function that attains a minimum value when the parameters of the demand model are closest to the predictions of the market model. This effective figure-of-merit function is minimized with respect to the demand model and market model parameters. The resulting demand model parameters conform to the portions of the sales history data that show a strong trend, and conform to the external market information when the corresponding portions of the sales history data show noise.
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Citations
18 Claims
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1. A computer-implemented method for tuning a demand model to a sales history that is stable with respect to random fluctuations in said sales history, said method comprising the steps of:
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providing a data storage having sales history data; selecting a demand model, said demand model depending on a plurality of parameters including at least one demand parameter; selecting a market model to describe how a subset of said at least one demand parameter is expected to vary according to external market information, said market model depending on at least one market parameter, which is external to said sales history data; constructing a an effective figure-of merit function from said demand model and said market model, said effective figure-of-merit function having a plurality of parameters including said at least one demand parameter and said at least one market parameter; and minimizing said effective figure-of-merit function with respect to said at least one demand parameter and said at lest one market parameter, thereby attaining an optimal value for said at least one demand parameter that is stable with respect to random fluctuations in said sales history data. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A computer-readable storage medium, for use in a computer having a storage device for storing sales history data, said computer-readable storage medium for storing program code for causing the computer to perform the steps of:
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selecting a demand model to predict the demand of a plurality of parameters including at least one demand parameter; selecting a market model to describe how a subset of said at least one demand parameter is expected to vary according to external market information, said market model depending on at least one market parameter, which is external to said sales history data; combining said demand model and said market model to from an effective figure-of-merit function; and minimizing said effective figure-of-merit function with respect to said at least one demand parameter and said at least one market parameter, thereby attaining an optimal value for said at least one demand parameter that is stable with respect to random fluctuations in said sales history data. - View Dependent Claims (11, 12, 13, 14, 15)
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16. A system for tuning a demand model to a sales history that stabilizes said demand model with respect to fluctuations in said sales history, said system for use with a storage device for storing sales history data, said system comprising:
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means for selecting a demand model and a market model, said demand model depending on a plurality of parameters including at least one demand parameter; wherein said market model describes how a subset of said at least one demand parameter is expected to vary according to external market information, said market model depending on at least one market parameter that is external to said sales history; means for combining said demand model and said market model to form an effective figure-of-merit function; and means for optimizing said at least one demand parameter in said effective figure-of-merit function that is stable with respect to random fluctuations in said sales history data. - View Dependent Claims (17, 18)
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Specification