A NEW PROBLEM FOR SELECTIVE MAINTENANCE CONSIDERING BI-
OBJECTIVES, REPAIRPERSON ASSIGNMENT AND K-OUT-OF-N SYSTEMS
Selective Maintenance. k-out-of-n systems. Metaheuristic. Matheuristic. Combinatorial Optimization.
This dissertation deals with the maintenance optimization problem in a multi-component
system, which should undergo maintenance actions between two consecutive missions,
preparing itself for the next mission. Due to time, budget and resource limitations, just a
subset of components and actions should be selected. Most of the existing models do not
tackle complex systems or, when they address this kind of system, they consider only one
objective to be optimized. Therefore, this work proposes a new non-linear binary model that
models the bi-Objective Selective Maintenance and Repairperson Assignment Problem on k- out-of-n complex systems (bi-OSMRAP:k-out-of-n). Its modeling is discussed, and three
algorithms are proposed for the problem solving: a full enumeration algorithm, a
metaheuristic and a matheuristic. Both approximated algorithms are based on the Adaptive
Variable Neighborhood Search. A sensitive analysis was conducted to understand the
problem behavior. Two instances were tested, one from the literature and an artificial instance.
Both approximated algorithms were solid and provided reasonable solutions, achieving more
than 65% optimization when we hypothesized that the decision-maker does not prefer one
objective over the other.