Exact lexicographic scheduling and approximate rescheduling

In industrial resource allocation problems, an initial planning stage may solve a nominal problem instance and subsequent recovery intervene to repair inefficiencies infeasibilities due uncertainty, e.g. machine failures job processing time variations. this context, we investigate the minimum makespan scheduling problem, a.k.a. P||Cmax, under uncertainty. We propose two-stage robust approach where first-stage decisions are computed with exact lexicographic second-stage derived using approximate rescheduling. explore strategies accounting for constrained by limited permitted deviations from original schedule. Our is substantiated analytically, price of robustness characterization parameterized degree numerically. This analysis based on optimal substructure imposed optimality. Thus, optimization enables more efficient Further, revisit state-of-the-art methods branch-and-bound algorithm whose performance validated computationally.