Optimization Proxies using Limited Labeled Data and Training Time -- A
Semi-Supervised Bayesian Neural Network Approach
Optimization Proxies using Limited Labeled Data and Training Time -- A
Semi-Supervised Bayesian Neural Network Approach
Constrained optimization problems arise in various engineering system operations such as inventory management and electric power grids. However, the requirement to repeatedly solve such optimization problems with uncertain parameters poses a significant computational challenge. This work introduces a learning scheme using Bayesian Neural Networks (BNNs) to solve constrained optimization problems …