The Optimization of Civil Aircraft Product Option Selection Considering the Economy Response with an Improved Non-Dominated Sorting Genetic Algorithm

To serve customized option selection for civil aircraft, a mathematical product option selection optimization model combined with an Improved Non-dominated Sorting Genetic Algorithm for decreasing aircraft fleet maintenance cost was investigated. For airlines, considering the economy and reliability in customized option selection is the most intuitive way to improve aircraft performance to generate the optimal formation configuration. Product option selection usually takes certain indicators as constraints (reliability and economy) to meet and maximize performance through equipment selection (the selected parameters include mean time between failures, price, etc.). To describe the customization needs of airlines by a mathematical model and find the optimal decision through an algorithm, a multi-objective, mathematical product option selection optimization model response with reliability parameters as a decision variable, maintainability as a link, and aircraft fleet maintenance and availability as an objective function is established to serve aircraft option selection in this paper. Next, the multi-objective genetic algorithm is used to solve the model, and the convergence, distribution and fitting accuracy of the objective functions are analyzed. Eventually, the landing gear system is used to verify the effectiveness of the model and method. After optimization, the aircraft fleet maintenance cost is reduced by 20.71%, and the availability is increased by 2.576%. Through the mathematical optimization model, the product configuration is provided for the development of the customization option selection project.