Optimizing Constrained C-Test Generation Using Mixed-Integer Programming

This work proposes a novel mixed-integer programming (MIP) approach to generate C-Tests, a type of gap-filling exercise, by simultaneously optimizing gap size and placement to achieve globally optimal solutions that satisfy explicit constraints.