Patent ID: 11915131
Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A computer-implemented method for utilizing a machine learning model to solve a sequential optimization problem, the method comprising:
receiving, by a computing device, a sequential optimization problem for solving;
utilizing, by the computing device, a learning based initializer and a gradient descent solver to solve a first instance of the sequential optimization problem;
learning, by the computing device a machine learning model, based on one or more solutions to the first instance of the sequential optimization problem, wherein learning by the computing device the machine learning model comprises:
sending the sequential optimization problem to the learning-based initializer and the gradient descent-based solver;
generating, by the learning-based initializer an initialization and sending the initialization to the gradient descent-based solver;
initiating, through the gradient descent-based solver, a search for a solution based on the initialization and an instance input;
sending, by the gradient descent-based solver, a current solution to an objective function, wherein the objective function returns a value of the objective function for the current solution to the gradient descent-based solve, and wherein the objective function is minimized and continuously differentiable for non-convex optimization; and
utilizing, through the gradient descent-based solver, the objective function to propose a next solution;

generating, by the computing device the machine learning model, one or more subsequent approximate solutions to the sequential optimization problem; and
outputting, by a user interface on the computing device, the one or more subsequent approximate solutions to the sequential optimization problem.