The Dual-Resource-Constrained Re-entrant Flexible Flow shop A Constraint Programming approach and a Hybrid Genetic Algorithm

The dual-resource-constrained re-entrant
exible
ow shop scheduling problem rep-
resents a specialized variant of the
ow shop scheduling problem, inspired by real-
world scenarios in screen printing industries. Besides the well-known
ow shop struc-
ture, stages consist of identical parallel machines and operations may re-enter the
same stage multiple times before completion. Moreover, each machine must be oper-
ated by a skilled worker, making it a dual-resource-constrained problem according to
the existing literature. The objective is to minimize the total length of the produc-
tion schedule. To address this problem, our study employs two methods: a constraint
programming model and a hybrid genetic algorithm with a single-level solution rep-
resentation and an ecient decoding heuristic. To evaluate the performance of our
methods, we conducted a computational study using dierent problem instances.
Our ndings demonstrate that the proposed hybrid genetic algorithm consistently
delivers high-quality solutions, particularly for large instances, while also maintain-
ing a short computational time. Additionally, our methods improve existing bench-
mark results for instances from the literature for a subclass of the problem. Further-
more, we provide managerial insights into how dual-resource constraints aect the
solution quality and the eciency associated with dierent workforce congurations
in the described production setting.