Learning the Fast Lane: When MILP Solvers Start Remembering Where the Answer Is
Opening — Why this matters now Mixed-Integer Linear Programming (MILP) sits quietly underneath a surprising amount of modern infrastructure: logistics routing, auctions, facility placement, chip layout, resource allocation. When it works, no one notices. When it doesn’t, the solver spins for hours, racks up nodes, and quietly burns money. At the center of this tension is branch-and-bound—an exact algorithm that is elegant in theory and painfully sensitive in practice. Its speed hinges less on raw compute than on where it looks first. For decades, that decision has been guided by human-designed heuristics: clever, brittle, and wildly inconsistent across problem families. ...