Robust permutation flow shop total weighted completion time problem: Solution and application to the oil and gas industry

Mario Levorato (1, 2, 3, 4) , David Sotelo (2) , Rosa Figueiredo (4) , Yuri Frota (3)

1 AU - Avignon Université
2 Petróleo Brasileiro S.A., Petrobras
3 IC-UFF - Instituto de Computação [Niteroi-Rio de Janeiro]
4 LIA - Laboratoire Informatique d'Avignon

This work proposes exact solution approaches for the m-machine robust permutation flow shop problem, where operation processing times are uncertain and vary in a given interval. Following the concept of budgeted uncertainty, the objective is to obtain a robust scheduling that minimizes the total weighted completion time of the restricted worst-case scenario, in which only a subset of operation processing times will deviate to worst-case values. We develop several robust counterpart formulations, which can be used to derive optimal solutions for medium-sized problem instances by using a Column-and-Constraint Generation algorithm. The efficacy of the solution methods is validated through experiments on three sets of randomly-generated instances. Finally, a case study for the maintenance schedule of Brazilian oil platforms is presented.

Mots clés: Scheduling Robust Optimization Permutation Flow Shop Total Weighted Completion Time Offshore platform maintenance; Scheduling; Robust Optimization; Permutation Flow Shop; Total Weighted Completion Time; Offshore platform maintenance

Domaines: Recherche opérationnelle [math.OC]; Modélisation et simulation

Mario Levorato, David Sotelo, Rosa Figueiredo, Yuri Frota. Robust permutation flow shop total weighted completion time problem: Solution and application to the oil and gas industry. Computers and Operations Research, 2023, 151, pp.106117. ⟨10.1016/j.cor.2022.106117⟩. ⟨hal-03891039⟩