RT Journal Article
T1 The Permutation Flow Shop Scheduling Problem with Human Resources: MILP Models, Decoding Procedures, NEH-Based Heuristics, and an Iterated Greedy Algorithm
A1 Fernandez-Viagas, Victor
A1 Sanchez-Mediano, Luis
A1 Angulo-Cortes, Alvaro
A1 Gomez-Medina, David
A1 Molina-Pariente, Jose Manuel
K1 scheduling
K1 flow shop
K1 MILP
K1 decoding procedure
K1 makespan
K1 flow shop
K1 human resources
K1 multiple servers
K1 sequence-dependent setups
K1 iterated greedy
K1 Dependent setup times
K1 Minimize makespan
K1 Machine
K1 Optimization
K1 Server
AB In this paper, we address the permutation flow shop scheduling problem with sequence-dependent and non-anticipatory setup times. These setups are performed or supervised by multiple servers, which are renewable secondary resources (typically human resources). Despite the real applications of this kind of human supervision and the growing attention paid in the scheduling literature, we are not aware of any previous study on the problem under consideration. To cover this gap, we start theoretically addressing the problem by: proposing three mixed-integer linear programming models to find optimal solutions in the problem; and proposing different decoding procedures to code solutions in approximated procedures. After that, the best decoding procedure is used to propose a new mechanism that generates 896 different dispatching rules, combining different measures, indicators, and sorting criteria. All these dispatching rules are embedded in the traditional NEH algorithm. Finally, an iterated greedy algorithm is proposed to find near-optimal solutions. By doing so, we provide academics and practitioners with efficient methods that can be used to obtain exact solutions of the problem; applied to quickly schedule jobs and react under changes; used for initialisation or embedded in more advanced algorithms; and/or easily updated and implemented in real manufacturing scenarios.
PB Mdpi
YR 2022
FD 2022-10-01
LK http://hdl.handle.net/10668/21414
UL http://hdl.handle.net/10668/21414
LA en
DS RISalud
RD Jun 1, 2025