公开(公告)号：US20250117552A1

公开(公告)日：2025-04-10

申请号：US18799055

申请日：2023-02-10

Applicant: The Trustees of Princeton University

Inventor： Prerit TERWAY ,  Niraj K. JHA

IPC: G06F30/27 ,  G06F111/06

Abstract: A design methodology and tool called INFORM are provided that use a two-phase approach for sample-efficient constrained multi-objective optimization of real-world nonlinear systems. In the first optional phase, one may modify a genetic algorithm (GA) to make the design process sample-efficient, and may inject candidate solutions into the GA population using inverse design methods. The inverse design techniques may be based on (i) a neural network verifier, (ii) a neural network, and (iii) a Gaussian mixture model. The candidate solutions for the next generation are thus a mix of those generated using crossover/mutation and solutions generated using inverse design. At the end of the first phase, one obtains a set of nondominated solutions. In the second phase, one chooses one or more solution(s) from the non-dominated solutions or another reference solution to further improve the objective function values using inverse design methods.