Integrating Analytic Hierarchy Process and Genetic Algorithm for Aircraft Engine Maintenance Scheduling Problem

Maintaining the reliability of aircraft engines in an acceptable level requires an optimal maintenance strategy and planning for each entity in the network. This paper proposes an analytic hierarchy process (AHP) and genetic algorithm (GA) hybrid model to deal with the maintenance scheduling problem of aircraft engine, which is an optimization problem formulated with respect to multiple objectives and soft constraints. GA, using an integer representation, is applied to obtain the best solution resulting in a minimal value of maintenance costs and time and maximal value of available cycles after maintenance in the analyzed period. AHP handles the decision-maker’s attitude toward preferences of the multiple objectives. The proposed method was tested using a maintenance company data for PW4077D engines and the obtained results show the feasibility and effectiveness of the approach for engine maintenance scheduling applications.

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