Metaheuristics for the online printing shop scheduling problem

In this work, the online printing shop scheduling problem is considered. This challenging real-world scheduling problem, that emerged in the present-day printing industry, corresponds to a flexible job shop scheduling problem with sequencing flexibility; and it presents several complicating requirements such as resumable operations, periods of unavailability of the machines, sequence-dependent setup times, partial overlapping between operations with precedence constraints, and fixed operations, among others. A local search strategy and metaheuristics are proposed and evaluated. Based on a common representation scheme, trajectory and populational metaheuristics are considered. Extensive numerical experiments on large-sized instances show that the proposed methods are suitable for solving practical instances of the problem; and that they outperform a half-heuristic-half-exact off-the-shelf solver by a large extent. In addition, numerical experiments on classical instances of the flexible job shop scheduling problem show that the proposed methods are also competitive when applied to this particular case.