Abstract: A method (and system) of providing optimization repeatability in an on-demand computing environment removes variability in an optimization model instance and can be exemplarily implemented in a service architecture. The method and system receives a plurality of physical data instances, which are different representations of the same logical data model, and transforms the plurality of physical data instances into a normalized physical data instance, which can be combined with an optimization model to form a unique optimization model instance, thereby providing repeatability in solving optimization problems.

Abstract: The present invention provides a system and method for strategic budgeting of initial response for managing wildfires. According to the present invention, stochastic-integer-programming-based constrained optimization techniques are employed to develop a strategic budget by optimally allocating disaster management resources to disaster events belonging to scenarios associated with occurrence probabilities. According to the invention, certain machine-readable data describing fires may be subjected to computerized data processing, ultimately producing a determination of valid disaster management resources for each fire event, which may be used for strategic budgeting of initial responses for managing wildfires.

Abstract: A computer implemented 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. The computer receives a set of functions representing a set of events where each function includes sets of first and second axis coordinate values. Each of the functions are transformed to a compacted function which includes a set of pieces including an anchor point, break points, and slopes. Successive pieces having the same slope value are removed. Alternate optimization models are generated based on the set of pieces representing a compacted function and on a predetermined accuracy value.

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.

Abstract: The present invention provides a system and method for strategic budgeting of initial response for managing wildfires. According to the present invention, stochastic-integer-programming-based constrained optimization techniques are employed to develop a strategic budget by optimally allocating disaster management resources to disaster events belonging to scenarios associated with occurrence probabilities. According to the invention, certain machine-readable data describing fires may be subjected to computerized data processing, ultimately producing a determination of valid disaster management resources for each fire event, which may be used for strategic budgeting of initial responses for managing wildfires.

Abstract: Development and use of a computer program in an arbitrary language are facilitated by representing expressions to be dynamically evaluated in a simple syntax compatible with a standard language. The method for evaluating the expressions must provide a pattern or template containing the form and syntax required for an embedded standard language query in the arbitrary language. The representation of the expression in the simple syntax is detected and the expression, variables contained in the expression and the name of the result of an evaluation of the expression are extracted and placed in the template or pattern to derive an intermediate form of the expression. Quantitative data developed by the computer program when it is run is substituted for the variables in the intermediate form of the expression to form a standard language query embedded in the arbitrary language program which is then evaluated by a standard language evaluation engine.

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.

Abstract: Development and use of a computer program, particularly for simulation or modeling, in an arbitrary language are facilitated by representing expressions to be dynamically evaluated in a simple syntax compatible with a standard language and providing a pattern or template in a form containing the form and syntax required for an embedded standard language query in the arbitrary language. The representation of the expression in the simple syntax is detected and the expression, variables contained in the expression and the name of the result of an evaluation of the expression are extracted and placed in the template or pattern to derive an intermediate form of the expression. Quantitative data developed by the computer program when it is run is substituted for the variables in the intermediate form of the expression to form a standard language query embedded in the arbitrary language program which is ten evaluated by a standard language evaluation engine.

Abstract: The present invention provides a system and method for strategic budgeting of initial response for managing wildfires. According to the present invention, stochastic-integer-programming-based constrained optimization techniques are employed to develop a strategic budget by optimally allocating disaster management resources to disaster events belonging to scenarios associated with occurrence probabilities. According to the invention, certain machine-readable data describing fires may be subjected to computerized data processing, ultimately producing a determination of valid disaster management resources for each fire event, which may be used for strategic budgeting of initial responses for managing wildfires.

Abstract: A method (and system) of providing optimization repeatability in an on-demand computing environment removes variability in an optimization model instance and can be exemplarily implemented in a service architecture. The method and system receives a plurality of physical data instances, which are different representations of the same logical data model, and transforms the plurality of physical data instances into a normalized physical data instance, which can be combined with an optimization model to form a unique optimization model instance, thereby providing repeatability in solving optimization problems.