Metaheuristics for the Online Printing Shop Scheduling Problem
  In this work, the online printing shop scheduling problem introduced in
(Lunardi et al., Mixed Integer Linear Programming and Constraint Programming
Models for the Online Printing Shop Scheduling Problem, Computers & Operations
Research, to appear) is considered. This challenging real scheduling problem,
that emerged in the nowadays printing industry, corresponds to a flexible job
shop scheduling problem with sequencing flexibility; and it presents several
complicating specificities 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 metaheuristic approaches
for the problem are proposed and evaluated. Based on a common representation
scheme, trajectory and populational metaheuristics are considered. Extensive
numerical experiments with 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.
Numerical experiments with classical instances of the flexible job shop
scheduling problem show that the introduced methods are also competitive when
applied to this particular case.
