Method and apparatus for generating alternative representation of optimization models

Abstract

A method for determining an alternative representation of an optimization model reduces model input through compact representation of model parameters. Model generation is performed at varying levels of complexity (approximation) depending on pre-defined, business approved thresholds.

1 . A computer implemented method for alternative model generation to solve optimization model instances having varying degrees of size and complexity comprising the steps of: 
 retrieving input data instances for an optimization model, wherein each input data instance contains multiple sets of input parameters;    compacting the input data by eliminating redundant data points while maintaining precision of an input function;    retrieving a pre-determined acceptable threshold for modifying model parameters; and    determining an optimal alternative representation of the optimization model while keeping parameters within the acceptable threshold.    
   
   
       2 . The computer implemented method of  claim 1 , wherein the input data instances comprise a set of functions having a set of x-axis values and a set of y-axis values, data points of y-axis values representing growth values and data points of x-axis values representing incremental time points, the step of compacting comprising generating a set of break-point values, a set of slope values for each piece defined by a breakpoint, and x and y coordinates of an anchor point.  
   
   
       3 . The computer implemented method of  claim 2 , wherein the step of determining an optimal alternative representation of the optimization model generates alternative models at varying levels of complexity depending on pre-determined acceptable thresholds.  
   
   
       4 . The computer implemented method of  claim 3 , further comprising the step of using the alternative representation to rebuild a new optimization model.  
   
   
       5 . The computer implemented method of  claim 3 , wherein the optimization model represents a problem of budgeting fire-management resources.  
   
   
       6 . A computer implemented alternative model generation mechanism for solving optimization model instances having varying degrees of size and complexity comprising: 
 a data transformer receiving retrieving input data instances for an optimization model, wherein each input data instance contains multiple sets of input parameters, said data transformer compacting the input data instances by eliminating redundant data points while maintaining precision of an input function;    an alternate model generator receiving output from the data transformer and a pre-determined accuracy threshold and generating output that enables model generation at various levels of complexity depending on pre-defined, business approved thresholds; and    a flexible optimization application which receives alternate data instances created as a result of using different threshold values in the alternate model generator and creates alternate optimization model instances.    
   
   
       7 . The computer implemented alternative model generation mechanism of  claim 6 , wherein the input data instances comprise a set of functions having a set of x-axis values and a set of y-axis values, data points of y-axis values representing growth values and data points of x-axis values representing incremental time points, and the data transformer compacts the input data instances by generating a set of break-point values, a set of slope values for each piece defined by a breakpoint, and x and y coordinates of an anchor point.  
   
   
       8 . The computer implemented alternative model generation mechanism of  claim 7 , wherein the flexible optimization application determines an optimal alternative representation of the optimization model and generates alternative models at varying levels of complexity depending on pre-determined acceptable thresholds.  
   
   
       9 . A computer readable medium containing code for alternative model generation to solve optimization model instances having varying degrees of size and complexity, the code implementing a method comprising the steps of: 
 retrieving input data instances for an optimization model, wherein each input data instance contains multiple sets of input parameters;    compacting the input data by eliminating redundant data points while maintaining precision of an input function;    retrieving a pre-determined acceptable threshold for modifying model parameters; and    determining an optimal alternative representation of the optimization model while keeping parameters within the acceptable threshold.    
   
   
       10 . The computer readable medium of  claim 9 , wherein the input data instances comprise a set of functions having a set of x-axis values and a set of y-axis values, data points of y-axis values representing growth values and data points of x-axis values representing incremental time points, the code implemented step of compacting comprising generating a set of break-point values, a set of slope values for each piece defined by a breakpoint, and x and y coordinates of an anchor point.