Multi-mission selective maintenance and repairpersons assignment problem with stochastic durations

Abstract

Systems are often required to execute a sequence of missions separated by scheduled breaks. To improve the success rate of the next mission, multi-mission selective maintenance is applied in the limited break. In general, the durations of missions, maintenance actions, and breaks are stochastic due to the influence of repairpersons, the environment, and so on. However, the existing researches rarely consider the stochasticity of these three kinds of durations in the multi-mission selective maintenance problem, which leads to the underestimation of the grand total cost and the neglect of its stochasticity. Besides, the real system reliability may be lower than the minimum requirement if the stochasticity of durations is ignored in the maintenance decision-making. To overcome the above problems, a new multi-mission selective maintenance and repairpersons assignment model with stochastic durations is developed. The proposed model is transformed into an optimization problem constrained by the limited maintenance resources, and the objective is to minimize the expected grand total cost with a given reliability threshold. Then, a tailored genetic algorithm with the initial population generated by the uniform design is proposed to solve the optimization problem. Finally, numerical examples are carried out to demonstrate the effectiveness of the proposed method.