Metaheuristics for the Online Printing Shop Scheduling Problem

TL;DR

This paper introduces metaheuristic algorithms to effectively solve the complex online printing shop scheduling problem, demonstrating their superiority over existing methods through extensive numerical experiments on large and classical instances.

Contribution

It proposes novel metaheuristic approaches tailored for the online printing shop scheduling problem, addressing its unique complexities and outperforming existing off-the-shelf solvers.

Findings

Metaheuristics outperform off-the-shelf solvers on large instances.

Proposed methods are competitive on classical flexible job shop problems.

Algorithms effectively handle complex scheduling constraints.

Abstract

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.