Patent Document ID: 7653522
Application ID: 11635206
Patent Flag: 1

Claim One:
1. A computer-implemented apparatus for robustness enhancing optimization of a physical system, comprising: a simulation-optimization computational engine implemented in the apparatus; a memory associated with said simulation-optimization computational engine for storing computation results; a data storage means for storing said computation results in said memory; a realization comprising a set of values of physical parameters for a model of the physical system; an optimization stopping criterion; a robustness evaluator; an optimizer in said simulation-optimization computational engine that develops an optimal strategy for each one of one or more primary objective functions, and modifies said strategy to increase the likelihood that the strategy will satisfy specified goals and constraints in the physical system without degrading primary objective function values beyond specified limits; wherein the apparatus performs robustness enhancing optimization by: (a) said optimizer in said simulation-optimization computational engine computing an optimal objective function value and a strategy comprising a set of values for decision variables for said realization; (b) said data storage means storing said computed strategy in said memory; (c) said robustness evaluator receiving said computed strategy; (d) said robustness evaluator evaluating robustness for said computed strategy by modifying said realization by multiplying the values of the set of physical parameters for the model by a factor smaller than 1 and determining that all constraints are maintained and the objective function value is within acceptable tolerance of the objective function value; (e) inputting output from said robustness evaluator to said simulation-optimization computational engine, performing optimization to improve the objective function value while satisfying constraints and computing a new strategy with a new set of decision variable values for said modified realization; (f) iterating through steps (b) through (e) using said new strategy as input to said computational engine until said optimization stopping criterion is met, resulting in at least one constraint violation; and (g) outputting a smallest multiplier for the physical parameter realization that still provides the objective function value within acceptable tolerance while maintaining all problem constraints.