Patent ID: 8185421

Claim:
In a constraint management system (CMS), a computer-implemented method of determining Pareto-optimal designs of a subject system, the method comprising, by a computer: representing a trade space in the CMS as a network of nodes including a plurality of variables, one or more auxiliary input parameters, and equality constraints defining relationships between the variables, wherein at least one variable is a user-selected independent variable and at least one variable is a user-selected dependent variable; determining a computational plan using the equality constraints for computing the at least one user-selected dependent variable from the at least one user-selected independent variable and the one or more auxiliary input parameters; performing an iterative multiple-objective optimization sampling procedure on the trade space to determine the Pareto-optimal designs, including: generating a set of designs, wherein each of the set of designs is associated with a value assigned to the at least one user-selected independent variable and a corresponding value computed for the at least one user-selected dependent variable using the computational plan, selecting a subset of the set of designs in accordance with an annealing schedule, perturbing the subset of designs to neighboring designs, evaluating the set of designs and neighboring designs using the computational plan, each design and neighboring design being associated with a value of the at least one user-selected independent variable and a corresponding value of the at least one user-selected dependent variable, determining a subset of the set of designs and neighboring designs that are Pareto-optimal; embedding in the network of nodes a constraint and a compound-valued variable representing the Pareto-optimal designs, wherein the constraint provides the Pareto-optimal designs for given values of the one or more auxiliary input parameters; automatically re-determining the Pareto-optimal designs using the constraint and compound-valued variable embedded in the network of nodes as values of the one or more auxiliary input parameters are varied; and reporting the set of Pareto-optimal designs.