A constrained genetic algorithm to optimize a maintenance global service

Abstract

It is herein developed an approach to optimize the maintenance services policy related to a Global Service Contract. In particular, the latter requires the performing of corrective maintenance and replacements of the failed components on a set of equal vehicles of a logistic Company. The tackled problem concerns the determination of an effective opportunistic maintenance policyon the basis of which when a fault occurs, it is replaced the failed component and, depending on the age of the others components, also replacements of others suitable components are performed, even if they are not yet broken, thus saving a substantial amount of system downtime. The problem is mathematically formulated by a constrained partition model aimed at the minimization of the global maintenance cost, which becomes difficult or very hard to solve by mathematical programming approach for large system as the one herein considered. For such reason, a suitable constrained genetic algorithm approach is employed to solve the considered problem. The performed optimization allows to point out components groups on which to perform maintenance actions when a system stop for failure occurs. In particular, a meaningful global maintenance cost reduction, up to 28%, can be obtained, thus demonstrating the effectiveness of the approach proposed.