Bi-objective workforce-constrained maintenance scheduling: a case study

• Published in: The Journal of the Operational Research Society Vol. 62; no. 6; pp. 1005 - 1018
• Main Authors: Safaei, N, Banjevic, D, Jardine, A K S
• Format: Journal Article
• Language: English
• Published: London Taylor & Francis 01.06.2011; Palgrave Macmillan; Palgrave Macmillan UK; Taylor & Francis Ltd
• Subjects: Aircraft; Applied sciences; bi-objective optimization; Breakdowns; Business and Management; Capital assets; Case studies; Case-oriented Paper; Case-oriented Papers; Completion costs; Cost control; Custodial services; Equipment failures; Exact sciences and technology; Failure; Firm modelling; Integer programming; Labor force; Maintenance; Maintenance management; Management; Mathematical programming; mixed-integer programming; Objective functions; Operational research and scientific management; Operational research. Management science; Operations research; Operations Research/Decision Theory; Optimization; Preventive maintenance; Railroad maintenance; Reliability theory. Replacement problems; Schedules; Scheduling; Scheduling, sequencing; Skilled workers; Skills; Studies; Workforce; workforce-constrained maintenance scheduling; Workloads; workforce-constrained maintenance scheduling; bi-objective optimization; mixed-integer programming; Availability; Sensitivity analysis; Priority; Multiobjective programming; Rupture; Mixed integer programming; Staff management; Scheduling; Maintenance; Failures; Modeling; Preventive maintenance; Optimization; Work team; Repair; Contract; Completion time
• ISSN: 0160-5682; 1476-9360
• DOI: 10.1057/jors.2010.51

In this paper, a real maintenance workforce-constrained scheduling problem is formulated as a bi-objective mixed-integer programming model with the aim of simultaneously minimizing the workforce requirements and maximizing the equipment availability. The skilled workforce is provided by internal and external resources using regular time, overtime and contracting. The equipment availability is measured by the downtime required for preventive maintenance (scheduled) and failure repair (unscheduled) jobs. We also encounter imminent or potential failures whose priorities depend on the severity of the failure on the system (secondary failure). The total weighted flow time is used as a scheduling criterion to measure the equipment availability; the weight of each job directly depends on the expected downtime resulting from the associated failure. The proposed model is verified using two comprehensive numerical examples and some sensitivity analyses. We conclude by discussing the results.