Robust permutation flow shop total weighted completion time problem: Solution and application to the oil and gas industry. (March 2023)

• Record Type: Journal Article
• Authors: Levorato, Mario; Sotelo, David; Figueiredo, Rosa; Frota, Yuri
• Is Part Of: Computers & operations research. Volume 151(2023)
• Publication Date: 2023-03
• Subjects: Scheduling -- Robust Optimization -- Permutation Flow Shop -- Total Weighted Completion Time -- Offshore platform maintenance; Operations research -- Periodicals; Electronic digital computers -- Periodicals; 004.05
• DOI: 10.1016/j.cor.2022.106117
• Languages: English
• ISSNs: 0305-0548

Abstract

Abstract: 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. Highlights: Robust flowshop with budget uncertainty minimize worst-case weighted completion time. Propose hybrid MILP and combinatorial-based branch-and-bound solution method. Propose seven robust counterpart models along with worst-case MILP formulation. Evaluate solution method and trade-off, including robustness price and hedge value. Case study compares obtained robust solutions to deterministic and stochastic ones.