Learning Capacity Constraints with Convex Neural Networks in Lot-Sizing Problems

This paper presents a novel approach for integrating convex neural networks into mixed-integer linear programs. We introduce a mixed-integer linear programming formulation that employs the Maxout activation function, and our experiments show that this network type outperforms rectified linear unit–b